Noise screen for attitude control system

NASA Technical Reports Server (NTRS)

Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Hong, David P. (Inventor); Hirschberg, Philip C. (Inventor)

2002-01-01

An attitude control system comprising a controller and a noise screen device coupled to the controller. The controller is adapted to control an attitude of a vehicle carrying an actuator system that is adapted to pulse in metered bursts in order to generate a control torque to control the attitude of the vehicle in response to a control pulse. The noise screen device is adapted to generate a noise screen signal in response to the control pulse that is generated when an input attitude error signal exceeds a predetermined deadband attitude level. The noise screen signal comprises a decaying offset signal that when combined with the attitude error input signal results in a net attitude error input signal away from the predetermined deadband level to reduce further control pulse generation.

Learning from adaptive neural dynamic surface control of strict-feedback systems.

PubMed

Wang, Min; Wang, Cong

2015-06-01

Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

DOE PAGES

Carlberg, Kevin T.

2014-11-05

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

Command generator tracker based direct model reference adaptive tracking guidance for Mars atmospheric entry

NASA Astrophysics Data System (ADS)

Li, Shuang; Peng, Yuming

2012-01-01

In order to accurately deliver an entry vehicle through the Martian atmosphere to the prescribed parachute deployment point, active Mars entry guidance is essential. This paper addresses the issue of Mars atmospheric entry guidance using the command generator tracker (CGT) based direct model reference adaptive control to reduce the adverse effect of the bounded uncertainties on atmospheric density and aerodynamic coefficients. Firstly, the nominal drag acceleration profile meeting a variety of constraints is planned off-line in the longitudinal plane as the reference model to track. Then, the CGT based direct model reference adaptive controller and the feed-forward compensator are designed to robustly track the aforementioned reference drag acceleration profile and to effectively reduce the downrange error. Afterwards, the heading alignment logic is adopted in the lateral plane to reduce the crossrange error. Finally, the validity of the guidance algorithm proposed in this paper is confirmed by Monte Carlo simulation analysis.

Mean deviation coupling synchronous control for multiple motors via second-order adaptive sliding mode control.

PubMed

Li, Lebao; Sun, Lingling; Zhang, Shengzhou

2016-05-01

A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Application of Transfer Matrix Approach to Modeling and Decentralized Control of Lattice-Based Structures

NASA Technical Reports Server (NTRS)

Cramer, Nick; Swei, Sean Shan-Min; Cheung, Kenny; Teodorescu, Mircea

2015-01-01

This paper presents a modeling and control of aerostructure developed by lattice-based cellular materials/components. The proposed aerostructure concept leverages a building block strategy for lattice-based components which provide great adaptability to varying ight scenarios, the needs of which are essential for in- ight wing shaping control. A decentralized structural control design is proposed that utilizes discrete-time lumped mass transfer matrix method (DT-LM-TMM). The objective is to develop an e ective reduced order model through DT-LM-TMM that can be used to design a decentralized controller for the structural control of a wing. The proposed approach developed in this paper shows that, as far as the performance of overall structural system is concerned, the reduced order model can be as e ective as the full order model in designing an optimal stabilizing controller.

Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping

2018-03-01

This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.

Some new results on stability and synchronization for delayed inertial neural networks based on non-reduced order method.

PubMed

Li, Xuanying; Li, Xiaotong; Hu, Cheng

2017-12-01

In this paper, without transforming the second order inertial neural networks into the first order differential systems by some variable substitutions, asymptotic stability and synchronization for a class of delayed inertial neural networks are investigated. Firstly, a new Lyapunov functional is constructed to directly propose the asymptotic stability of the inertial neural networks, and some new stability criteria are derived by means of Barbalat Lemma. Additionally, by designing a new feedback control strategy, the asymptotic synchronization of the addressed inertial networks is studied and some effective conditions are obtained. To reduce the control cost, an adaptive control scheme is designed to realize the asymptotic synchronization. It is noted that the dynamical behaviors of inertial neural networks are directly analyzed in this paper by constructing some new Lyapunov functionals, this is totally different from the traditional reduced-order variable substitution method. Finally, some numerical simulations are given to demonstrate the effectiveness of the derived theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive suboptimal second-order sliding mode control for microgrids

NASA Astrophysics Data System (ADS)

Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

2016-09-01

This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

Simulation to coating weight control for galvanizing

NASA Astrophysics Data System (ADS)

Wang, Junsheng; Yan, Zhang; Wu, Kunkui; Song, Lei

2013-05-01

Zinc coating weight control is one of the most critical issues for continuous galvanizing line. The process has the characteristic of variable-time large time delay, nonlinear, multivariable. It can result in seriously coating weight error and non-uniform coating. We develop a control system, which can automatically control the air knives pressure and its position to give a constant and uniform zinc coating, in accordance with customer-order specification through an auto-adaptive empirical model-based feed forward adaptive controller, and two model-free adaptive feedback controllers . The proposed models with controller were applied to continuous galvanizing line (CGL) at Angang Steel Works. By the production results, the precise and stability of the control model reduces over-coating weight and improves coating uniform. The product for this hot dip galvanizing line does not only satisfy the customers' quality requirement but also save the zinc consumption.

Utilizing adaptive wing technology in the control of a micro air vehicle

NASA Astrophysics Data System (ADS)

Null, William R.; Wagner, Matthew G.; Shkarayev, Sergey V.; Jouse, Wayne C.; Brock, Keith M.

2002-07-01

Evolution of the design of micro air vehicles (MAVs) towards miniaturization has been severely constrained by the size and mass of the electronic components needed to control the vehicles. Recent research, experimentation, and development in the area of smart materials have led to the possibility of embedding control actuators, fabricated from smart materials, in the wing of the vehicle, reducing both the size and mass of these components. Further advantages can be realized by developing adaptive wing structures. Small size and mass, and low airspeeds, can lead to considerable buffeting during flight, and may result in a loss of flight control. In order to counter these effects, we are developing a thin, variable-cambered airfoil design with actuators embedded within the wing. In addition to reducing the mass and size of the vehicle or, conversely, increasing its available payload, an important benefit from the adaptive wing concept is the possibility of in-flight modification of the flight envelope. Reduced airspeeds, which are crucial during loiter, can be realized by an in-flight increase in wing camber. Conversely, decreases in camber provide for an airframe best suited for rapid ingress/egress and extension of the mission range.

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

PubMed

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Adaptive model-predictive controller for magnetic resonance guided focused ultrasound therapy.

PubMed

de Bever, Joshua; Todd, Nick; Payne, Allison; Christensen, Douglas A; Roemer, Robert B

2014-11-01

Minimising treatment time and protecting healthy tissues are conflicting goals that play major roles in making magnetic resonance image-guided focused ultrasound (MRgFUS) therapies clinically practical. We have developed and tested in vivo an adaptive model-predictive controller (AMPC) that reduces treatment time, ensures safety and efficacy, and provides flexibility in treatment set-up. The controller realises time savings by modelling the heated treatment cell's future temperatures and thermal dose accumulation in order to anticipate the optimal time to switch to the next cell. Selected tissues are safeguarded by a configurable temperature constraint. Simulations quantified the time savings realised by each controller feature as well as the trade-offs between competing safety and treatment time parameters. In vivo experiments in rabbit thighs established the controller's effectiveness and reliability. In all in vivo experiments the target thermal dose of at least 240 CEM43 was delivered everywhere in the treatment volume. The controller's temperature safety limit reliably activated and constrained all protected tissues to <9 CEM43. Simulations demonstrated the path independence of the controller, and that a path which successively proceeds to the hottest untreated neighbouring cell leads to significant time savings, e.g. when compared to a concentric spiral path. Use of the AMPC produced a compounding time-saving effect; reducing the treatment cells' heating times concurrently reduced heating of normal tissues, which eliminated cooling periods. Adaptive model-predictive control can automatically deliver safe, effective MRgFUS treatments while significantly reducing treatment times.

Digital controllers for VTOL aircraft

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.; Berry, P. W.

1976-01-01

Using linear-optimal estimation and control techniques, digital-adaptive control laws have been designed for a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for non-zero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.

Advanced Wavefront Control Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olivier, S S; Brase, J M; Avicola, K

2001-02-21

Programs at LLNL that involve large laser systems--ranging from the National Ignition Facility to new tactical laser weapons--depend on the maintenance of laser beam quality through precise control of the optical wavefront. This can be accomplished using adaptive optics, which compensate for time-varying aberrations that are often caused by heating in a high-power laser system. Over the past two decades, LLNL has developed a broad capability in adaptive optics technology for both laser beam control and high-resolution imaging. This adaptive optics capability has been based on thin deformable glass mirrors with individual ceramic actuators bonded to the back. In themore » case of high-power lasers, these adaptive optics systems have successfully improved beam quality. However, as we continue to extend our applications requirements, the existing technology base for wavefront control cannot satisfy them. To address this issue, this project studied improved modeling tools to increase our detailed understanding of the performance of these systems, and evaluated novel approaches to low-order wavefront control that offer the possibility of reduced cost and complexity. We also investigated improved beam control technology for high-resolution wavefront control. Many high-power laser systems suffer from high-spatial-frequency aberrations that require control of hundreds or thousands of phase points to provide adequate correction. However, the cost and size of current deformable mirrors can become prohibitive for applications requiring more than a few tens of phase control points. New phase control technologies are becoming available which offer control of many phase points with small low-cost devices. The goal of this project was to expand our wavefront control capabilities with improved modeling tools, new devices that reduce system cost and complexity, and extensions to high spatial and temporal frequencies using new adaptive optics technologies. In FY 99, the second year of this project, work was performed in four areas (1) advanced modeling tools for deformable mirrors (2) low-order wavefront correctors with Alvarez lenses, (3) a direct phase measuring heterdyne wavefront sensor, and (4) high-spatial-frequency wavefront control using spatial light modulators.« less

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS.

PubMed

Wang, Jianlin; Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system.

Nonlinear model predictive control for chemical looping process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng

A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to amore » CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.« less

An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1984-01-01

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Conflict adaptation and congruency sequence effects to social-emotional stimuli in individuals with autism spectrum disorders.

PubMed

Worsham, Whitney; Gray, Whitney E; Larson, Michael J; South, Mikle

2015-11-01

The modification of performance following conflict can be measured using conflict adaptation tasks thought to measure the change in the allocation of cognitive resources in order to reduce conflict interference and improve performance. While previous studies have suggested atypical processing during nonsocial cognitive control tasks, conflict adaptation (i.e. congruency sequence effects) for social-emotional stimuli have not been previously studied in autism spectrum disorder. A total of 32 participants diagnosed with autism spectrum disorder and 27 typically developing matched controls completed an emotional Stroop conflict task that required the classification of facial affect while simultaneously ignoring an overlaid affective word. Both groups showed behavioral evidence for emotional conflict adaptation based on response times and accuracy rates. However, the autism spectrum disorder group demonstrated a speed-accuracy trade-off manifested through significantly faster response times and decreased accuracy rates on trials containing conflict between the emotional face and the overlaid emotional word. Reduced selective attention toward socially relevant information may bias individuals with autism spectrum disorder toward more rapid processing and decision making even when conflict is present. Nonetheless, the loss of important information from the social stimuli reduces decision-making accuracy, negatively affecting the ability to adapt both cognitively and emotionally when conflict arises. © The Author(s) 2014.

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS

PubMed Central

Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system. PMID:29702696

Applied adaptive disturbance rejection using output redefinition on magnetic bearings

NASA Astrophysics Data System (ADS)

Matras, Alex Logan

Recent work has shown Adaptive Disturbance Rejection to be an effective technique for rejecting forces due to imbalance, runout and base motion disturbances on flywheels supported by magnetic bearings over a large span of frequencies. Often the applicability of some of the adaptive methods is limited because they require certain properties (such as almost-strict positive realness) that magnetic bearings do not possess. In this thesis, one method for adaptive disturbance rejection, called Adaptive Feedforward Cancellation (AFC), is modified to allow for a much wider range of frequencies to be rejected. This is accomplished by redefining the output of the original system to be the output from a reduced order state estimator instead. This can give a new system with an infinite gain margin. Additionally, the adaptation laws for the two disturbance rejection gains are slightly modified so that each adapts to a different signal in order to provide the best performance. A detailed model of a magnetic bearing is developed and computer simulations based on that model are performed to give an initial test of the new control law. A state-of-the-art magnetic bearing setup is then developed and used to implement the new control laws and determine their effectiveness. The results are successful and validate the new ideas that are presented.

Functional Based Adaptive and Fuzzy Sliding Controller for Non-Autonomous Active Suspension System

NASA Astrophysics Data System (ADS)

Huang, Shiuh-Jer; Chen, Hung-Yi

In this paper, an adaptive sliding controller is developed for controlling a vehicle active suspension system. The functional approximation technique is employed to substitute the unknown non-autonomous functions of the suspension system and release the model-based requirement of sliding mode control algorithm. In order to improve the control performance and reduce the implementation problem, a fuzzy strategy with online learning ability is added to compensate the functional approximation error. The update laws of the functional approximation coefficients and the fuzzy tuning parameters are derived from the Lyapunov theorem to guarantee the system stability. The proposed controller is implemented on a quarter-car hydraulic actuating active suspension system test-rig. The experimental results show that the proposed controller suppresses the oscillation amplitude of the suspension system effectively.

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

NASA Astrophysics Data System (ADS)

Yue, Fengfa; Li, Xingfei; Chen, Cheng; Tan, Wenbin

2017-12-01

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.

Aperiodic linear networked control considering variable channel delays: application to robots coordination.

PubMed

Santos, Carlos; Espinosa, Felipe; Santiso, Enrique; Mazo, Manuel

2015-05-27

One of the main challenges in wireless cyber-physical systems is to reduce the load of the communication channel while preserving the control performance. In this way, communication resources are liberated for other applications sharing the channel bandwidth. The main contribution of this work is the design of a remote control solution based on an aperiodic and adaptive triggering mechanism considering the current network delay of multiple robotics units. Working with the actual network delay instead of the maximum one leads to abandoning this conservative assumption, since the triggering condition is fixed depending on the current state of the network. This way, the controller manages the usage of the wireless channel in order to reduce the channel delay and to improve the availability of the communication resources. The communication standard under study is the widespread IEEE 802.11g, whose channel delay is clearly uncertain. First, the adaptive self-triggered control is validated through the TrueTime simulation tool configured for the mentioned WiFi standard. Implementation results applying the aperiodic linear control laws on four P3-DX robots are also included. Both of them demonstrate the advantage of this solution in terms of network accessing and control performance with respect to periodic and non-adaptive self-triggered alternatives.

The performance of a reduced-order adaptive controller when used in multi-antenna hyperthermia treatments with nonlinear temperature-dependent perfusion.

PubMed

Cheng, Kung-Shan; Yuan, Yu; Li, Zhen; Stauffer, Paul R; Maccarini, Paolo; Joines, William T; Dewhirst, Mark W; Das, Shiva K

2009-04-07

In large multi-antenna systems, adaptive controllers can aid in steering the heat focus toward the tumor. However, the large number of sources can greatly increase the steering time. Additionally, controller performance can be degraded due to changes in tissue perfusion which vary non-linearly with temperature, as well as with time and spatial position. The current work investigates whether a reduced-order controller with the assumption of piecewise constant perfusion is robust to temperature-dependent perfusion and achieves steering in a shorter time than required by a full-order controller. The reduced-order controller assumes that the optimal heating setting lies in a subspace spanned by the best heating vectors (virtual sources) of an initial, approximate, patient model. An initial, approximate, reduced-order model is iteratively updated by the controller, using feedback thermal images, until convergence of the heat focus to the tumor. Numerical tests were conducted in a patient model with a right lower leg sarcoma, heated in a 10-antenna cylindrical mini-annual phased array applicator operating at 150 MHz. A half-Gaussian model was used to simulate temperature-dependent perfusion. Simulated magnetic resonance temperature images were used as feedback at each iteration step. Robustness was validated for the controller, starting from four approximate initial models: (1) a 'standard' constant perfusion lower leg model ('standard' implies a model that exactly models the patient with the exception that perfusion is considered constant, i.e., not temperature dependent), (2) a model with electrical and thermal tissue properties varied from 50% higher to 50% lower than the standard model, (3) a simplified constant perfusion pure-muscle lower leg model with +/-50% deviated properties and (4) a standard model with the tumor position in the leg shifted by 1.5 cm. Convergence to the desired focus of heating in the tumor was achieved for all four simulated models. The controller accomplished satisfactory therapeutic outcomes: approximately 80% of the tumor was heated to temperatures 43 degrees C and approximately 93% was maintained at temperatures <41 degrees C. Compared to the controller without model reduction, a approximately 9-25 fold reduction in convergence time was accomplished using approximately 2-3 orthonormal virtual sources. In the situations tested, the controller was robust to the presence of temperature-dependent perfusion. The results of this work can help to lay the foundation for real-time thermal control of multi-antenna hyperthermia systems in clinical situations where perfusion can change rapidly with temperature.

Development of an adaptive hp-version finite element method for computational optimal control

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Warner, Michael S.

1994-01-01

In this research effort, the usefulness of hp-version finite elements and adaptive solution-refinement techniques in generating numerical solutions to optimal control problems has been investigated. Under NAG-939, a general FORTRAN code was developed which approximated solutions to optimal control problems with control constraints and state constraints. Within that methodology, to get high-order accuracy in solutions, the finite element mesh would have to be refined repeatedly through bisection of the entire mesh in a given phase. In the current research effort, the order of the shape functions in each element has been made a variable, giving more flexibility in error reduction and smoothing. Similarly, individual elements can each be subdivided into many pieces, depending on the local error indicator, while other parts of the mesh remain coarsely discretized. The problem remains to reduce and smooth the error while still keeping computational effort reasonable enough to calculate time histories in a short enough time for on-board applications.

Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator.

PubMed

Nguyen, Sy Dzung; Vo, Hoang Duy; Seo, Tae-Il

2017-09-01

It is difficult to efficiently control nonlinear systems in the presence of uncertainty and disturbance (UAD). One of the main reasons derives from the negative impact of the unknown features of UAD as well as the response delay of the control system on the accuracy rate in the real time of the control signal. In order to deal with this, we propose a new controller named CO-FSMC for a class of nonlinear control systems subjected to UAD, which is constituted of a fuzzy sliding mode controller (FSMC) and a fuzzy-based compensator (CO). Firstly, the FSMC and CO are designed independently, and then an adaptive fuzzy structure is discovered to combine them. Solutions for avoiding the singular cases of the fuzzy-based function approximation and reducing the calculating cost are proposed. Based on the solutions, fuzzy sliding mode technique, lumped disturbance observer and Lyapunov stability analysis, a closed-loop adaptive control law is formulated. Simulations along with a real application based on a semi-active train-car suspension are performed to fully evaluate the method. The obtained results reflected that vibration of the chassis mass is insensitive to UAD. Compared with the other fuzzy sliding mode control strategies, the CO-FSMC can provide the best control ability to reduce unwanted vibrations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Active Control of Fan-Generated Tone Noise

NASA Technical Reports Server (NTRS)

Gerhold, Carl H.

1995-01-01

This paper reports on an experiment to control the noise radiated from the inlet of a ducted fan using a time domain active adaptive system. The control ,sound source consists of loudspeakers arranged in a ring around the fan duct. The error sensor location is in the fan duct. The purpose of this experiment is to demonstrate that the in-duct error sensor reduces the mode spillover in the far field, thereby increasing the efficiency of the control system. The control system is found to reduce the blade passage frequency tone significantly in the acoustic far field when the mode orders of the noise source and of the control source are the same, when the dominant wave in the duct is a plane wave. The presence of higher order modes in the duct reduces the noise reduction efficiency, particularly near the mode cut-on where the standing wave component is strong, but the control system converges stably. The control system is stable and converges when the first circumferential mode is generated in the duct. The control system is found to reduce the fan noise in the far field on an arc around the fan inlet by as much as 20 dB with none of the sound amplification associated with mode spillover.

Observer-based adaptive backstepping control for fractional order systems with input saturation.

PubMed

Sheng, Dian; Wei, Yiheng; Cheng, Songsong; Wang, Yong

2017-07-03

An observer-based fractional order anti-saturation adaptive backstepping control scheme is proposed for incommensurate fractional order systems with input saturation and partial measurable state in this paper. On the basis of stability analysis, a novel state observer is established first since the only information we could acquire is the system output. In order to compensate the saturation, a series of virtual signals are generated via the construction of fractional order auxiliary system. Afterwards, the controller design is carried out in accordance with the adaptive backstepping control method by introduction of the indirect Lyapunov method. To highlight the effectiveness of the proposed control scheme, simulation examples are demonstrated at last. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Controls for space structures

NASA Astrophysics Data System (ADS)

Balas, Mark

1991-11-01

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control.

Controls for space structures

NASA Technical Reports Server (NTRS)

Balas, Mark

1991-01-01

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control. A theory for disturbance accommodating controllers based on reduced order models of structures was developed, and stability results for these controllers in closed-loop with large-scale finite element models of structures were obtained.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Reduced short term adaptation to robot generated dynamic environment in children affected by Cerebral Palsy.

PubMed

Masia, Lorenzo; Frascarelli, Flaminia; Morasso, Pietro; Di Rosa, Giuseppe; Petrarca, Maurizio; Castelli, Enrico; Cappa, Paolo

2011-05-21

It is known that healthy adults can quickly adapt to a novel dynamic environment, generated by a robotic manipulandum as a structured disturbing force field. We suggest that it may be of clinical interest to evaluate to which extent this kind of motor learning capability is impaired in children affected by cerebal palsy. We adapted the protocol already used with adults, which employs a velocity dependant viscous field, and compared the performance of a group of subjects affected by Cerebral Palsy (CP group, 7 subjects) with a Control group of unimpaired age-matched children. The protocol included a familiarization phase (FA), during which no force was applied, a force field adaptation phase (CF), and a wash-out phase (WO) in which the field was removed. During the CF phase the field was shut down in a number of randomly selected "catch" trials, which were used in order to evaluate the "learning index" for each single subject and the two groups. Lateral deviation, speed and acceleration peaks and average speed were evaluated for each trajectory; a directional analysis was performed in order to inspect the role of the limb's inertial anisotropy in the different experimental phases. During the FA phase the movements of the CP subjects were more curved, displaying greater and variable directional error; over the course of the CF phase both groups showed a decreasing trend in the lateral error and an after-effect at the beginning of the wash-out, but the CP group had a non significant adaptation rate and a lower learning index, suggesting that CP subjects have reduced ability to learn to compensate external force. Moreover, a directional analysis of trajectories confirms that the control group is able to better predict the force field by tuning the kinematic features of the movements along different directions in order to account for the inertial anisotropy of arm. Spatial abnormalities in children affected by cerebral palsy may be related not only to disturbance in motor control signals generating weakness and spasticity, but also to an inefficient control strategy which is not based on a robust knowledge of the dynamical features of their upper limb. This lack of information could be related to the congenital nature of the brain damage and may contribute to a better delineation of therapeutic intervention.

A Reconfiguration Scheme for Accommodating Actuator Failures in Multi-Input, Multi-Output Flight Control Systems

NASA Technical Reports Server (NTRS)

Siwakosit, W.; Hess, R. A.; Bacon, Bart (Technical Monitor); Burken, John (Technical Monitor)

2000-01-01

A multi-input, multi-output reconfigurable flight control system design utilizing a robust controller and an adaptive filter is presented. The robust control design consists of a reduced-order, linear dynamic inversion controller with an outer-loop compensation matrix derived from Quantitative Feedback Theory (QFT). A principle feature of the scheme is placement of the adaptive filter in series with the QFT compensator thus exploiting the inherent robustness of the nominal flight control system in the presence of plant uncertainties. An example of the scheme is presented in a pilot-in-the-loop computer simulation using a simplified model of the lateral-directional dynamics of the NASA F18 High Angle of Attack Research Vehicle (HARV) that included nonlinear anti-wind up logic and actuator limitations. Prediction of handling qualities and pilot-induced oscillation tendencies in the presence of these nonlinearities is included in the example.

Autonomous Pointing Control of a Large Satellite Antenna Subject to Parametric Uncertainty

PubMed Central

Wu, Shunan; Liu, Yufei; Radice, Gianmarco; Tan, Shujun

2017-01-01

With the development of satellite mobile communications, large antennas are now widely used. The precise pointing of the antenna’s optical axis is essential for many space missions. This paper addresses the challenging problem of high-precision autonomous pointing control of a large satellite antenna. The pointing dynamics are firstly proposed. The proportional–derivative feedback and structural filter to perform pointing maneuvers and suppress antenna vibrations are then presented. An adaptive controller to estimate actual system frequencies in the presence of modal parameters uncertainty is proposed. In order to reduce periodic errors, the modified controllers, which include the proposed adaptive controller and an active disturbance rejection filter, are then developed. The system stability and robustness are analyzed and discussed in the frequency domain. Numerical results are finally provided, and the results have demonstrated that the proposed controllers have good autonomy and robustness. PMID:28287450

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

PubMed

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

Chaos Suppression in Fractional order Permanent Magnet Synchronous Generator in Wind Turbine Systems

NASA Astrophysics Data System (ADS)

Rajagopal, Karthikeyan; Karthikeyan, Anitha; Duraisamy, Prakash

2017-06-01

In this paper we investigate the control of three-dimensional non-autonomous fractional-order uncertain model of a permanent magnet synchronous generator (PMSG) via a adaptive control technique. We derive a dimensionless fractional order model of the PMSM from the integer order presented in the literatures. Various dynamic properties of the fractional order model like eigen values, Lyapunov exponents, bifurcation and bicoherence are investigated. The system chaotic behavior for various orders of fractional calculus are presented. An adaptive controller is derived to suppress the chaotic oscillations of the fractional order model. As the direct Lyapunov stability analysis of the robust controller is difficult for a fractional order first derivative, we have derived a new lemma to analyze the stability of the system. Numerical simulations of the proposed chaos suppression methodology are given to prove the analytical results derived through which we show that for the derived adaptive controller and the parameter update law, the origin of the system for any bounded initial conditions is asymptotically stable.

Adaptive variable structure hierarchical fuzzy control for a class of high-order nonlinear dynamic systems.

PubMed

Mansouri, Mohammad; Teshnehlab, Mohammad; Aliyari Shoorehdeli, Mahdi

2015-05-01

In this paper, a novel adaptive hierarchical fuzzy control system based on the variable structure control is developed for a class of SISO canonical nonlinear systems in the presence of bounded disturbances. It is assumed that nonlinear functions of the systems be completely unknown. Switching surfaces are incorporated into the hierarchical fuzzy control scheme to ensure the system stability. A fuzzy soft switching system decides the operation area of the hierarchical fuzzy control and variable structure control systems. All the nonlinearly appeared parameters of conclusion parts of fuzzy blocks located in different layers of the hierarchical fuzzy control system are adjusted through adaptation laws deduced from the defined Lyapunov function. The proposed hierarchical fuzzy control system reduces the number of rules and consequently the number of tunable parameters with respect to the ordinary fuzzy control system. Global boundedness of the overall adaptive system and the desired precision are achieved using the proposed adaptive control system. In this study, an adaptive hierarchical fuzzy system is used for two objectives; it can be as a function approximator or a control system based on an intelligent-classic approach. Three theorems are proven to investigate the stability of the nonlinear dynamic systems. The important point about the proposed theorems is that they can be applied not only to hierarchical fuzzy controllers with different structures of hierarchical fuzzy controller, but also to ordinary fuzzy controllers. Therefore, the proposed algorithm is more general. To show the effectiveness of the proposed method four systems (two mechanical, one mathematical and one chaotic) are considered in simulations. Simulation results demonstrate the validity, efficiency and feasibility of the proposed approach to control of nonlinear dynamic systems. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

PubMed

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Convergence of fractional adaptive systems using gradient approach.

PubMed

Gallegos, Javier A; Duarte-Mermoud, Manuel A

2017-07-01

Conditions for boundedness and convergence of the output error and the parameter error for various Caputo's fractional order adaptive schemes based on the steepest descent method are derived in this paper. To this aim, the concept of sufficiently exciting signals is introduced, characterized and related to the concept of persistently exciting signals used in the integer order case. An application is designed in adaptive indirect control of integer order systems using fractional equations to adjust parameters. This application is illustrated for a pole placement adaptive problem. Advantages of using fractional adjustment in control adaptive schemes are experimentally obtained. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Neural adaptive control for vibration suppression in composite fin-tip of aircraft.

PubMed

Suresh, S; Kannan, N; Sundararajan, N; Saratchandran, P

2008-06-01

In this paper, we present a neural adaptive control scheme for active vibration suppression of a composite aircraft fin tip. The mathematical model of a composite aircraft fin tip is derived using the finite element approach. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes very accurately. Piezo-electric actuators and sensors are placed at optimal locations such that the vibration suppression is a maximum. Model-reference direct adaptive neural network control scheme is proposed to force the vibration level within the minimum acceptable limit. In this scheme, Gaussian neural network with linear filters is used to approximate the inverse dynamics of the system and the parameters of the neural controller are estimated using Lyapunov based update law. In order to reduce the computational burden, which is critical for real-time applications, the number of hidden neurons is also estimated in the proposed scheme. The global asymptotic stability of the overall system is ensured using the principles of Lyapunov approach. Simulation studies are carried-out using sinusoidal force functions of varying frequency. Experimental results show that the proposed neural adaptive control scheme is capable of providing significant vibration suppression in the multiple bending modes of interest. The performance of the proposed scheme is better than the H(infinity) control scheme.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Adaptive mechanisms of insect pests against plant protease inhibitors and future prospects related to crop protection: a review.

PubMed

Macedo, Maria L R; de Oliveira, Caio F R; Costa, Poliene M; Castelhano, Elaine C; Silva-Filho, Marcio C

2015-01-01

The overwhelming demand for food requires the application of technology on field. An important issue that limits the productivity of crops is related to insect attacks. Hence, several studies have evaluated the application of different compounds to reduce the field losses, especially insecticide compounds from plant sources. Among them, plant protease inhibitors (PIs) have been studied in both basic and applied researches, displaying positive results in control of some insects. However, certain species are able to bypass the insecticide effects exerted by PIs. In this review, we disclosed the adaptive mechanisms showed by lepidopteran and coleopteran insects, the most expressive insect orders related to crop predation. The structural aspects involved in adaptation mechanisms are presented as well as the newest alternatives for pest control. The application of biotechnological tools in crop protection will be mandatory in agriculture, and it will be up to researchers to find the best candidates for effective control in long-term.

Development of adaptive observation strategy using retrospective optimal interpolation

NASA Astrophysics Data System (ADS)

Noh, N.; Kim, S.; Song, H.; Lim, G.

2011-12-01

Retrospective optimal interpolation (ROI) is a method that is used to minimize cost functions with multiple minima without using adjoint models. Song and Lim (2011) perform the experiments to reduce the computational costs for implementing ROI by transforming the control variables into eigenvectors of background error covariance. We adapt the ROI algorithm to compute sensitivity estimates of severe weather events over the Korean peninsula. The eigenvectors of the ROI algorithm is modified every time the observations are assimilated. This implies that the modified eigenvectors shows the error distribution of control variables which are updated by assimilating observations. So, We can estimate the effects of the specific observations. In order to verify the adaptive observation strategy, High-impact weather over the Korean peninsula is simulated and interpreted using WRF modeling system and sensitive regions for each high-impact weather is calculated. The effects of assimilation for each observation type is discussed.

Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Boskovic, Jovan D.

2008-01-01

This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

Design of the Electronic Brake Pressure Modulator Using a Direct Adaptive Fuzzy Controller in Commercial Vehicles for the Safety of Braking in Fail

NASA Astrophysics Data System (ADS)

Kim, Hunmo

In the brake systems, it is important to reduce the rear brake pressure in order to secure the safety of the vehicle in braking. So, there was some research that reduced and controlled the rear brake pressure exactly like a L. S. P. V and a E. L. S. P. V. However, the previous research has some weaknesses: the L. S. P. V is a mechanical system and its brake efficiency is lower than the efficiency of E. L. S. P. V. But, the cost of E. L. S. P. V is very higher so its application to the vehicle is very difficult. Additionally, when a fail appears in the circuit which controls the valves, the fail results in some wrong operation of the valves. But, the previous researchers didn't take the effect of fail into account. Hence, the efficiency of them is low and the safety of the vehicle is not confirmed. So, in this paper we develop a new economical pressure modulator that exactly controls brake pressure and confirms the safety of the vehicle in any case using a direct adaptive fuzzy controller.

Adaptive vibration control using synchronous demodulation with machine tool controller motor commutation

DOEpatents

Hopkins, David James [Livermore, CA

2008-05-13

A control system and method for actively reducing vibration in a spindle housing caused by unbalance forces on a rotating spindle, by measuring the force-induced spindle-housing motion, determining control signals based on synchronous demodulation, and provide compensation for the measured displacement to cancel or otherwise reduce or attenuate the vibration. In particular, the synchronous demodulation technique is performed to recover a measured spindle housing displacement signal related only to the rotation of a machine tool spindle, and consequently rejects measured displacement not related to spindle motion or synchronous to a cycle of revolution. Furthermore, the controller actuates at least one voice-coil (VC) motor, to cancel the original force-induced motion, and adapts the magnitude of voice coil signal until this measured displacement signal is brought to a null. In order to adjust the signal to a null, it must have the correct phase relative to the spindle angle. The feedback phase signal is used to adjust a common (to both outputs) commutation offset register (offset relative to spindle encoder angle) to force the feedback phase signal output to a null. Once both of these feedback signals are null, the system is compensating properly for the spindle-induced motion.

Neuromechanical evidence of improved neuromuscular control around knee joint in volleyball players.

PubMed

Masci, Ilaria; Vannozzi, Giuseppe; Gizzi, Leonardo; Bellotti, Pasquale; Felici, Francesco

2010-02-01

The aim of the present work was to verify that skilled volleyball players present specific adaptations in both neuromuscular control and movement biomechanics, showing an improved neuromuscular control around the knee joint than in non-jumper athletes. Seven male volleyball players and seven male non-jumper athletes were recruited for this study. The following tests were performed in a random order: single countermovement jump (CMJ), single squat jump. At the end of the series, subjects performed a repetitive CMJ test. Electromyographic signals were recorded from vastus lateralis and biceps femoris muscles on both sides. Ground reaction forces and moments were measured with a force plate. Volleyball athletes performed better in all tests and were more resistant to fatigue than non-jumper athletes. Furthermore, volleyball athletes showed a reduced co-activation of knee flexor/extensor muscles. The present results seem to stand for a neural adaptation of the motor control scheme to training.

A decentralized linear quadratic control design method for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1990-01-01

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass and stiffness properties.

Feedforward compensation control of rotor imbalance for high-speed magnetically suspended centrifugal compressors using a novel adaptive notch filter

NASA Astrophysics Data System (ADS)

Zheng, Shiqiang; Feng, Rui

2016-03-01

This paper introduces a feedforward control strategy combined with a novel adaptive notch filter to solve the problem of rotor imbalance in high-speed Magnetically Suspended Centrifugal Compressors (MSCCs). Unbalance vibration force of rotor in MSCC is mainly composed of current stiffness force and displacement stiffness force. In this paper, the mathematical model of the unbalance vibration with the proportional-integral-derivative (PID) control laws is presented. In order to reduce the unbalance vibration, a novel adaptive notch filter is proposed to identify the synchronous frequency displacement of the rotor as a compensation signal to eliminate the current stiffness force. In addition, a feedforward channel from position component to control output is introduced to compensate displacement stiffness force to achieve a better performance. A simplified inverse model of power amplifier is included in the feedforward channel to reject the degrade performance caused by its low-pass characteristic. Simulation and experimental results on a MSCC demonstrate a significant effect on the synchronous vibration suppression of the magnetically suspended rotor at a high speed.

A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

PubMed Central

Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah

2015-01-01

A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

2014-07-01

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

Evaluation of microfabricated deformable mirror systems

NASA Astrophysics Data System (ADS)

Cowan, William D.; Lee, Max K.; Bright, Victor M.; Welsh, Byron M.

1998-09-01

This paper presents recent result for aberration correction and beam steering experiments using polysilicon surface micromachined piston micromirror arrays. Microfabricated deformable mirrors offer a substantial cost reduction for adaptive optic systems. In addition to the reduced mirror cost, microfabricated mirrors typically require low control voltages, thus eliminating high voltage amplifiers. The greatly reduced cost per channel of adaptive optic systems employing microfabricated deformable mirrors promise high order aberration correction at low cost. Arrays of piston micromirrors with 128 active elements were tested. Mirror elements are on a 203 micrometers 12 by 12 square grid. The overall array size is 2.4 mm square. The arrays were fabricated in the commercially available DARPA supported MUMPs surface micromachining foundry process. The cost per mirror array in this prototyping process is less than 200 dollars. Experimental results are presented for a hybrid correcting element comprised of a lenslet array and piston micromirror array, and for a piston micromirror array only. Also presented is a novel digital deflection micromirror which requires no digital to analog converters, further reducing the cost of adaptive optics system.

Active control of fan-generated plane wave noise

NASA Technical Reports Server (NTRS)

Gerhold, Carl H.; Nuckolls, William E.; Santamaria, Odillyn L.; Martinson, Scott D.

1993-01-01

Subsonic propulsion systems for future aircraft may incorporate ultra-high bypass ratio ducted fan engines whose dominant noise source is the fan with blade passage frequency less than 1000 Hz. This low frequency combines with the requirement of a short nacelle to diminish the effectiveness of passive duct liners. Active noise control is seen as a viable method to augment the conventional passive treatments. An experiment to control ducted fan noise using a time domain active adaptive system is reported. The control sound source consists of loudspeakers arrayed around the fan duct. The error sensor location is in the fan duct. The purpose of this experiment is to demonstrate that the in-duct error sensor reduces the mode spillover in the far field, thereby increasing the efficiency of the control system. In this first series of tests, the fan is configured so that predominantly zero order circumferential waves are generated. The control system is found to reduce the blade passage frequency tone significantly in the acoustic far field when the mode orders of the noise source and of the control source are the same. The noise reduction is not as great when the mode orders are not the same even though the noise source modes are evanescent, but the control system converges stably and global noise reduction is demonstrated in the far field. Further experimentation is planned in which the performance of the system will be evaluated when higher order radial and spinning modes are generated.

A comparison of two adaptive algorithms for the control of active engine mounts

NASA Astrophysics Data System (ADS)

Hillis, A. J.; Harrison, A. J. L.; Stoten, D. P.

2005-08-01

This paper describes work conducted in order to control automotive active engine mounts, consisting of a conventional passive mount and an internal electromagnetic actuator. Active engine mounts seek to cancel the oscillatory forces generated by the rotation of out-of-balance masses within the engine. The actuator generates a force dependent on a control signal from an algorithm implemented with a real-time DSP. The filtered-x least-mean-square (FXLMS) adaptive filter is used as a benchmark for comparison with a new implementation of the error-driven minimal controller synthesis (Er-MCSI) adaptive controller. Both algorithms are applied to an active mount fitted to a saloon car equipped with a four-cylinder turbo-diesel engine, and have no a priori knowledge of the system dynamics. The steady-state and transient performance of the two algorithms are compared and the relative merits of the two approaches are discussed. The Er-MCSI strategy offers significant computational advantages as it requires no cancellation path modelling. The Er-MCSI controller is found to perform in a fashion similar to the FXLMS filter—typically reducing chassis vibration by 50-90% under normal driving conditions.

Multi Car Elevator Control by using Learning Automaton

NASA Astrophysics Data System (ADS)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

Shape control of structures with semi-definite stiffness matrices for adaptive wings

NASA Astrophysics Data System (ADS)

Austin, Fred; Van Nostrand, William C.; Rossi, Michael J.

1993-09-01

Maintaining an optimum-wing cross section during transonic cruise can dramatically reduce the shock-induced drag and can result in significant fuel savings and increased range. Our adaptive-wing concept employs actuators as truss elements of active ribs to reshape the wing cross section by deforming the structure. In our previous work, to derive the shape control- system gain matrix, we developed a procedure that requires the inverse of the stiffness matrix of the structure without the actuators. However, this method cannot be applied to designs where the actuators are required structural elements since the stiffness matrices are singular when the actuator are removed. Consequently, a new method was developed, where the order of the problem is reduced and only the inverse of a small nonsingular partition of the stiffness matrix is required to obtain the desired gain matrix. The procedure was experimentally validated by achieving desired shapes of a physical model of an aircraft-wing rib. The theory and test results are presented.

Quaternion error-based optimal control applied to pinpoint landing

NASA Astrophysics Data System (ADS)

Ghiglino, Pablo

Accurate control techniques for pinpoint planetary landing - i.e., the goal of achieving landing errors in the order of 100m for unmanned missions - is a complex problem that have been tackled in different ways in the available literature. Among other challenges, this kind of control is also affected by the well known trade-off in UAV control that for complex underlying models the control is sub-optimal, while optimal control is applied to simplifed models. The goal of this research has been the development new control algorithms that would be able to tackle these challenges and the result are two novel optimal control algorithms namely: OQTAL and HEX2OQTAL. These controllers share three key properties that are thoroughly proven and shown in this thesis; stability, accuracy and adaptability. Stability is rigorously demonstrated for both controllers. Accuracy is shown in results of comparing these novel controllers with other industry standard algorithms in several different scenarios: there is a gain in accuracy of at least 15% for each controller, and in many cases much more than that. A new tuning algorithm based on swarm heuristics optimisation was developed as well as part of this research in order to tune in an online manner the standard Proportional-Integral-Derivative (PID) controllers used for benchmarking. Finally, adaptability of these controllers can be seen as a combination of four elements: mathematical model extensibility, cost matrices tuning, reduced computation time required and finally no prior knowledge of the navigation or guidance strategies needed. Further simulations in real planetary landing trajectories has shown that these controllers have the capacity of achieving landing errors in the order of pinpoint landing requirements, making them not only very precise UAV controllers, but also potential candidates for pinpoint landing unmanned missions.

Reinforcement-learning-based dual-control methodology for complex nonlinear discrete-time systems with application to spark engine EGR operation.

PubMed

Shih, Peter; Kaul, Brian C; Jagannathan, S; Drallmeier, James A

2008-08-01

A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary one for the affine nonlinear discrete-time system but the controllers together offer the desired performance. The primary adaptive critic NN controller includes an NN observer for estimating the states and output, an NN critic, and two action NNs for generating virtual control and actual control inputs for the nonstrict feedback nonlinear discrete-time system, whereas an additional critic NN and an action NN are included for the affine nonlinear discrete-time system by assuming the state availability. All NN weights adapt online towards minimization of a certain performance index, utilizing gradient-descent-based rule. Using Lyapunov theory, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error, weight estimates, and observer estimates are shown. The adaptive critic NN controller performance is evaluated on an SI engine operating with high EGR levels where the controller objective is to reduce cyclic dispersion in heat release while minimizing fuel intake. Simulation and experimental results indicate that engine out emissions drop significantly at 20% EGR due to reduction in dispersion in heat release thus verifying the dual-control approach.

A reduced energy supply strategy in active vibration control

NASA Astrophysics Data System (ADS)

Ichchou, M. N.; Loukil, T.; Bareille, O.; Chamberland, G.; Qiu, J.

2011-12-01

In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings.

Dynamic Analysis and Adaptive Sliding Mode Controller for a Chaotic Fractional Incommensurate Order Financial System

NASA Astrophysics Data System (ADS)

Hajipour, Ahmad; Tavakoli, Hamidreza

2017-12-01

In this study, the dynamic behavior and chaos control of a chaotic fractional incommensurate-order financial system are investigated. Using well-known tools of nonlinear theory, i.e. Lyapunov exponents, phase diagrams and bifurcation diagrams, we observe some interesting phenomena, e.g. antimonotonicity, crisis phenomena and route to chaos through a period doubling sequence. Adopting largest Lyapunov exponent criteria, we find that the system yields chaos at the lowest order of 2.15. Next, in order to globally stabilize the chaotic fractional incommensurate order financial system with uncertain dynamics, an adaptive fractional sliding mode controller is designed. Numerical simulations are used to demonstrate the effectiveness of the proposed control method.

Second-order sliding mode controller with model reference adaptation for automatic train operation

NASA Astrophysics Data System (ADS)

Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

2017-11-01

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

An Adaptive Coordinated Control for an Offshore Wind Farm Connected VSC Based Multi-Terminal DC Transmission System

NASA Astrophysics Data System (ADS)

Kumar, M. Ajay; Srikanth, N. V.

2015-01-01

The voltage source converter (VSC) based multiterminal high voltage direct current (MTDC) transmission system is an interesting technical option to integrate offshore wind farms with the onshore grid due to its unique performance characteristics and reduced power loss via extruded DC cables. In order to enhance the reliability and stability of the MTDC system, an adaptive neuro fuzzy inference system (ANFIS) based coordinated control design has been addressed in this paper. A four terminal VSC-MTDC system which consists of an offshore wind farm and oil platform is implemented in MATLAB/ SimPowerSystems software. The proposed model is tested under different fault scenarios along with the converter outage and simulation results show that the novel coordinated control design has great dynamic stabilities and also the VSC-MTDC system can supply AC voltage of good quality to offshore loads during the disturbances.

On decentralized adaptive full-order sliding mode control of multiple UAVs.

PubMed

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Experimental study of an adaptive CFRC reflector for high order wave-front error correction

NASA Astrophysics Data System (ADS)

Lan, Lan; Fang, Houfei; Wu, Ke; Jiang, Shuidong; Zhou, Yang

2018-03-01

The recent radio frequency communication system developments are generating the need for creating space antennas with lightweight and high precision. The carbon fiber reinforced composite (CFRC) materials have been used to manufacture the high precision reflector. The wave-front errors caused by fabrication and on-orbit distortion are inevitable. The adaptive CFRC reflector has received much attention to do the wave-front error correction. Due to uneven stress distribution that is introduced by actuation force and fabrication, the high order wave-front errors such as print-through error is found on the reflector surface. However, the adaptive CFRC reflector with PZT actuators basically has no control authority over the high order wave-front errors. A new design architecture assembled secondary ribs at the weak triangular surfaces is presented in this paper. The virtual experimental study of the new adaptive CFRC reflector has conducted. The controllability of the original adaptive CFRC reflector and the new adaptive CFRC reflector with secondary ribs are investigated. The virtual experimental investigation shows that the new adaptive CFRC reflector is feasible and efficient to diminish the high order wave-front error.

Digital multi-channel high resolution phase locked loop for surveillance radar systems

NASA Astrophysics Data System (ADS)

Rizk, Mohamed; Shaaban, Shawky; Abou-El-Nadar, Usama M.; Hafez, Alaa El-Din Sayed

This paper present a multi-channel, high resolution, fast lock phase locked loop (PLL) for surveillance radar applications. Phase detector based PLLs are simple to design, suffer no systematic phase error, and can run at the highest speed. Reducing loop gain can proportionally improve jitter performance, but also reduces locking time and pull-in range. The proposed system is based on digital process and control the error signal to the voltage controlled oscillator (VCO) adaptively to control its gain in order to achieve fast lock times while improving in lock jitter performance. Under certain circumstances the design also improves the frequency agility capability of the radar system. The results show a fast lock, high resolution PLL with transient time less than 10 µ sec which is suitable to radar applications.

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

2002-01-01

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Switching Reinforcement Learning for Continuous Action Space

NASA Astrophysics Data System (ADS)

Nagayoshi, Masato; Murao, Hajime; Tamaki, Hisashi

Reinforcement Learning (RL) attracts much attention as a technique of realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL into practical use. This difficulty includes a problem of designing a suitable action space of an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, we propose switching RL model to mimic a process of an infant's motor development in which gross motor skills develop before fine motor skills. Then, a method for switching controllers is constructed by introducing and referring to the “entropy”. Further, through computational experiments by using robot navigation problems with one and two-dimensional continuous action space, the validity of the proposed method has been confirmed.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1973-01-01

A survey of the literature in which Liapunov's second method is used in determining the control law is presented, with emphasis placed on the model-tracking adaptive control problem. Forty references are listed. Following a brief tutorial exposition of the adaptive control problem, the techniques for treating reduction of order, disturbance and time-varying parameters, multivariable systems, identification, and adaptive observers are discussed. The method is critically evaluated, particularly with respect to possibilities for application.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hexacopter trajectory control using a neural network

NASA Astrophysics Data System (ADS)

Artale, V.; Collotta, M.; Pau, G.; Ricciardello, A.

2013-10-01

The modern flight control systems are complex due to their non-linear nature. In fact, modern aerospace vehicles are expected to have non-conventional flight envelopes and, then, they must guarantee a high level of robustness and adaptability in order to operate in uncertain environments. Neural Networks (NN), with real-time learning capability, for flight control can be used in applications with manned or unmanned aerial vehicles. Indeed, using proven lower level control algorithms with adaptive elements that exhibit long term learning could help in achieving better adaptation performance while performing aggressive maneuvers. In this paper we show a mathematical modeling and a Neural Network for a hexacopter dynamics in order to develop proper methods for stabilization and trajectory control.

Gait Planning and Stability Control of a Quadruped Robot

PubMed Central

Li, Junmin; Wang, Jinge; Yang, Simon X.; Zhou, Kedong; Tang, Huijuan

2016-01-01

In order to realize smooth gait planning and stability control of a quadruped robot, a new controller algorithm based on CPG-ZMP (central pattern generator-zero moment point) is put forward in this paper. To generate smooth gait and shorten the adjusting time of the model oscillation system, a new CPG model controller and its gait switching strategy based on Wilson-Cowan model are presented in the paper. The control signals of knee-hip joints are obtained by the improved multi-DOF reduced order control theory. To realize stability control, the adaptive speed adjustment and gait switch are completed by the real-time computing of ZMP. Experiment results show that the quadruped robot's gaits are efficiently generated and the gait switch is smooth in the CPG control algorithm. Meanwhile, the stability of robot's movement is improved greatly with the CPG-ZMP algorithm. The algorithm in this paper has good practicability, which lays a foundation for the production of the robot prototype. PMID:27143959

Gait Planning and Stability Control of a Quadruped Robot.

PubMed

Li, Junmin; Wang, Jinge; Yang, Simon X; Zhou, Kedong; Tang, Huijuan

2016-01-01

In order to realize smooth gait planning and stability control of a quadruped robot, a new controller algorithm based on CPG-ZMP (central pattern generator-zero moment point) is put forward in this paper. To generate smooth gait and shorten the adjusting time of the model oscillation system, a new CPG model controller and its gait switching strategy based on Wilson-Cowan model are presented in the paper. The control signals of knee-hip joints are obtained by the improved multi-DOF reduced order control theory. To realize stability control, the adaptive speed adjustment and gait switch are completed by the real-time computing of ZMP. Experiment results show that the quadruped robot's gaits are efficiently generated and the gait switch is smooth in the CPG control algorithm. Meanwhile, the stability of robot's movement is improved greatly with the CPG-ZMP algorithm. The algorithm in this paper has good practicability, which lays a foundation for the production of the robot prototype.

Autonomous emergency braking systems adapted to snowy road conditions improve drivers' perceived safety and trust.

PubMed

Koglbauer, Ioana; Holzinger, Jürgen; Eichberger, Arno; Lex, Cornelia

2018-04-03

This study investigated drivers' evaluation of a conventional autonomous emergency braking (AEB) system on high and reduced tire-road friction and compared these results to those of an AEB system adaptive to the reduced tire-road friction by earlier braking. Current automated systems such as the AEB do not adapt the vehicle control strategy to the road friction; for example, on snowy roads. Because winter precipitation is associated with a 19% increase in traffic crashes and a 13% increase in injuries compared to dry conditions, the potential of conventional AEB to prevent collisions could be significantly improved by including friction in the control algorithm. Whereas adaption is not legally required for a conventional AEB system, higher automated functions will have to adapt to the current tire-road friction because human drivers will not be required to monitor the driving environment at all times. For automated driving functions to be used, high levels of perceived safety and trust of occupants have to be reached with new systems. The application case of an AEB is used to investigate drivers' evaluation depending on the road condition in order to gain knowledge for the design of future driving functions. In a driving simulator, the conventional, nonadaptive AEB was evaluated on dry roads with high friction (μ = 1) and on snowy roads with reduced friction (μ = 0.3). In addition, an AEB system adapted to road friction was designed for this study and compared with the conventional AEB on snowy roads with reduced friction. Ninety-six drivers (48 males, 48 females) assigned to 5 age groups (20-29, 30-39, 40-49, 50-59, and 60-75 years) drove with AEB in the simulator. The drivers observed and evaluated the AEB's braking actions in response to an imminent rear-end collision at an intersection. The results show that drivers' safety and trust in the conventional AEB were significantly lower on snowy roads, and the nonadaptive autonomous braking strategy was considered less appropriate on snowy roads compared to dry roads. As expected, the adaptive AEB braking strategy was considered more appropriate for snowy roads than the nonadaptive strategy. In conditions of reduced friction, drivers' subjective safety and trust were significantly improved when driving with the adaptive AEB compared to the conventional AEB. Women felt less safe than men when AEB was braking. Differences between age groups were not of statistical significance. Drivers notice the adaptation of the autonomous braking strategy on snowy roads with reduced friction. On snowy roads, they feel safer and trust the adaptive system more than the nonadaptive automation.

Adaptable and adaptive materials for light flux control

NASA Astrophysics Data System (ADS)

Sixou, Pierre; Magnaldo, A.; Nourry, J.; Laye, C.

1996-04-01

The purpose of this paper is to describe and examine properties of light flux control materials. Indeed, intelligent light flux control is necessary not only to improve everyday visual convenience but also in an economical point of view in order to reduce global home energetic cost. Several types of materials are good potential candidates for such functions: (1) The most well-known investigations concern inorganic materials such as tungsten or molybdenum oxides in which an electrochrom layer darkens when enriched in ions, and looses its color when impoverished. Unfortunately, at the moment, there is no convenient way to realize correct ions suppliers. Moreover, other drawbacks arise, such as poor reversibility, reactive interferences or a sensitivity of the material to its environment. These systems only need a low voltage level to work. But, their dynamic response, which is correlated to the component surface, is quite long. (2) At the present time, another attractive issue seems promising. More and more studies concern micro-composite liquid crystal films. For first, we shall remind their principles as well as their way of preparation. After having talked about their main advantages as intelligent materials, we shall discuss their control, their light flux adaptability, or their memory capabilities.

Recurrent myocardial infarction: Mechanisms of free-floating adaptation and autonomic derangement in networked cardiac neural control.

PubMed

Kember, Guy; Ardell, Jeffrey L; Shivkumar, Kalyanam; Armour, J Andrew

2017-01-01

The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as 'free-floating' in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease.

Efficacy of Coming Out Proud to reduce stigma's impact among people with mental illness: pilot randomised controlled trial.

PubMed

Rüsch, Nicolas; Abbruzzese, Elvira; Hagedorn, Eva; Hartenhauer, Daniel; Kaufmann, Ilias; Curschellas, Jan; Ventling, Stephanie; Zuaboni, Gianfranco; Bridler, René; Olschewski, Manfred; Kawohl, Wolfram; Rössler, Wulf; Kleim, Birgit; Corrigan, Patrick W

2014-01-01

Facing frequent stigma and discrimination, many people with mental illness have to choose between secrecy and disclosure in different settings. Coming Out Proud (COP), a 3-week peer-led group intervention, offers support in this domain in order to reduce stigma's negative impact. To examine COP's efficacy to reduce negative stigma-related outcomes and to promote adaptive coping styles (Current Controlled Trials number: ISRCTN43516734). In a pilot randomised controlled trial, 100 participants with mental illness were assigned to COP or a treatment-as-usual control condition. Outcomes included self-stigma, empowerment, stigma stress, secrecy and perceived benefits of disclosure. Intention-to-treat analyses found no effect of COP on self-stigma or empowerment, but positive effects on stigma stress, disclosure-related distress, secrecy and perceived benefits of disclosure. Some effects diminished during the 3-week follow-up period. Coming Out Proud has immediate positive effects on disclosure- and stigma stress-related variables and may thus alleviate stigma's negative impact.

Enhanced vaccine control of epidemics in adaptive networks

NASA Astrophysics Data System (ADS)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Enhanced vaccine control of epidemics in adaptive networks.

PubMed

Shaw, Leah B; Schwartz, Ira B

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Predicting mesh density for adaptive modelling of the global atmosphere.

PubMed

Weller, Hilary

2009-11-28

The shallow water equations are solved using a mesh of polygons on the sphere, which adapts infrequently to the predicted future solution. Infrequent mesh adaptation reduces the cost of adaptation and load-balancing and will thus allow for more accurate mapping on adaptation. We simulate the growth of a barotropically unstable jet adapting the mesh every 12 h. Using an adaptation criterion based largely on the gradient of the vorticity leads to a mesh with around 20 per cent of the cells of a uniform mesh that gives equivalent results. This is a similar proportion to previous studies of the same test case with mesh adaptation every 1-20 min. The prediction of the mesh density involves solving the shallow water equations on a coarse mesh in advance of the locally refined mesh in order to estimate where features requiring higher resolution will grow, decay or move to. The adaptation criterion consists of two parts: that resolved on the coarse mesh, and that which is not resolved and so is passively advected on the coarse mesh. This combination leads to a balance between resolving features controlled by the large-scale dynamics and maintaining fine-scale features.

Applying Computer Models to Realize Closed-Loop Neonatal Oxygen Therapy.

PubMed

Morozoff, Edmund; Smyth, John A; Saif, Mehrdad

2017-01-01

Within the context of automating neonatal oxygen therapy, this article describes the transformation of an idea verified by a computer model into a device actuated by a computer model. Computer modeling of an entire neonatal oxygen therapy system can facilitate the development of closed-loop control algorithms by providing a verification platform and speeding up algorithm development. In this article, we present a method of mathematically modeling the system's components: the oxygen transport within the patient, the oxygen blender, the controller, and the pulse oximeter. Furthermore, within the constraints of engineering a product, an idealized model of the neonatal oxygen transport component may be integrated effectively into the control algorithm of a device, referred to as the adaptive model. Manual and closed-loop oxygen therapy performance were defined in this article by 3 criteria in the following order of importance: percent duration of SpO2 spent in normoxemia (target SpO2 ± 2.5%), hypoxemia (less than normoxemia), and hyperoxemia (more than normoxemia); number of 60-second periods <85% SpO2 and >95% SpO2; and number of manual adjustments. Results from a clinical evaluation that compared the performance of 3 closed-loop control algorithms (state machine, proportional-integral-differential, and adaptive model) with manual oxygen therapy on 7 low-birth-weight ventilated preterm babies, are presented. Compared with manual therapy, all closed-loop control algorithms significantly increased the patients' duration in normoxemia and reduced hyperoxemia (P < 0.05). The number of manual adjustments was also significantly reduced by all of the closed-loop control algorithms (P < 0.05). Although the performance of the 3 control algorithms was equivalent, it is suggested that the adaptive model, with its ease of use, may have the best utility.

Robust Adaptive Control Using a Filtering Action

DTIC Science & Technology

2009-09-01

research performed on this class of control systems , sensitivity to external disturbances and modeling errors together with poor transient response...dissertation, we address the problems of designing a class of Adaptive Control systems which yield fast adaptation, thus good transient response, and...unable to stabilize the system . Although this approach requires more knowledge about the system in order to control it, it is still attractive in cases

The influence of approach-avoidance motivational orientation on conflict adaptation.

PubMed

Hengstler, Maikel; Holland, Rob W; van Steenbergen, Henk; van Knippenberg, Ad

2014-06-01

To deal effectively with a continuously changing environment, our cognitive system adaptively regulates resource allocation. Earlier findings showed that an avoidance orientation (induced by arm extension), relative to an approach orientation (induced by arm flexion), enhanced sustained cognitive control. In avoidance conditions, performance on a cognitive control task was enhanced, as indicated by a reduced congruency effect, relative to approach conditions. Extending these findings, in the present behavioral studies we investigated dynamic adaptations in cognitive control-that is, conflict adaptation. We proposed that an avoidance state recruits more resources in response to conflicting signals, and thereby increases conflict adaptation. Conversely, in an approach state, conflict processing diminishes, which consequently weakens conflict adaptation. As predicted, approach versus avoidance arm movements affected both behavioral congruency effects and conflict adaptation: As compared to approach, avoidance movements elicited reduced congruency effects and increased conflict adaptation. These results are discussed in line with a possible underlying neuropsychological model.

Design and analysis of adaptive Super-Twisting sliding mode control for a microgyroscope.

PubMed

Feng, Zhilin; Fei, Juntao

2018-01-01

This paper proposes a novel adaptive Super-Twisting sliding mode control for a microgyroscope under unknown model uncertainties and external disturbances. In order to improve the convergence rate of reaching the sliding surface and the accuracy of regulating and trajectory tracking, a high order Super-Twisting sliding mode control strategy is employed, which not only can combine the advantages of the traditional sliding mode control with the Super-Twisting sliding mode control, but also guarantee that the designed control system can reach the sliding surface and equilibrium point in a shorter finite time from any initial state and avoid chattering problems. In consideration of unknown parameters of micro gyroscope system, an adaptive algorithm based on Lyapunov stability theory is designed to estimate the unknown parameters and angular velocity of microgyroscope. Finally, the effectiveness of the proposed scheme is demonstrated by simulation results. The comparative study between adaptive Super-Twisting sliding mode control and conventional sliding mode control demonstrate the superiority of the proposed method.

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Modified Adaptive Control for Region 3 Operation in the Presence of Wind Turbine Structural Modes

NASA Technical Reports Server (NTRS)

Frost, Susan Alane; Balas, Mark J.; Wright, Alan D.

2010-01-01

Many challenges exist for the operation of wind turbines in an efficient manner that is reliable and avoids component fatigue and failure. Turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, possibly causing component fatigue and failure. Wind turbine manufacturers are highly motivated to reduce component fatigue and failure that can lead to loss of revenue due to turbine down time and maintenance costs. The trend in wind turbine design is toward larger, more flexible turbines that are ideally suited to adaptive control methods due to the complexity and expense required to create accurate models of their dynamic characteristics. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the excitation of structural modes in the wind turbine. The control objective is accomplished by collectively pitching the turbine blades. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. The adaptive controller will demonstrate the ability to regulate generator speed in Region 3, while accommodating gusts, and reducing the excitation of certain structural modes in the wind turbine.

Bacteriophages and Bacterial Plant Diseases

PubMed Central

Buttimer, Colin; McAuliffe, Olivia; Ross, R. P.; Hill, Colin; O’Mahony, Jim; Coffey, Aidan

2017-01-01

Losses in crop yields due to disease need to be reduced in order to meet increasing global food demands associated with growth in the human population. There is a well-recognized need to develop new environmentally friendly control strategies to combat bacterial crop disease. Current control measures involving the use of traditional chemicals or antibiotics are losing their efficacy due to the natural development of bacterial resistance to these agents. In addition, there is an increasing awareness that their use is environmentally unfriendly. Bacteriophages, the viruses of bacteria, have received increased research interest in recent years as a realistic environmentally friendly means of controlling bacterial diseases. Their use presents a viable control measure for a number of destructive bacterial crop diseases, with some phage-based products already becoming available on the market. Phage biocontrol possesses advantages over chemical controls in that tailor-made phage cocktails can be adapted to target specific disease-causing bacteria. Unlike chemical control measures, phage mixtures can be easily adapted for bacterial resistance which may develop over time. In this review, we will examine the progress and challenges for phage-based disease biocontrol in food crops. PMID:28163700

Decomposed fuzzy systems and their application in direct adaptive fuzzy control.

PubMed

Hsueh, Yao-Chu; Su, Shun-Feng; Chen, Ming-Chang

2014-10-01

In this paper, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator for adaptive fuzzy control systems. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables form the so-called component fuzzy systems. DFS is proposed to provide more adjustable parameters to facilitate possible adaptation in fuzzy rules, but without introducing a learning burden. It is because those component fuzzy systems are independent so that it can facilitate minimum distribution learning effects among component fuzzy systems. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this paper to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure.

Fixed gain and adaptive techniques for rotorcraft vibration control

NASA Technical Reports Server (NTRS)

Roy, R. H.; Saberi, H. A.; Walker, R. A.

1985-01-01

The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

Multi-objective Optimization Design of Gear Reducer Based on Adaptive Genetic Algorithms

NASA Astrophysics Data System (ADS)

Li, Rui; Chang, Tian; Wang, Jianwei; Wei, Xiaopeng; Wang, Jinming

2008-11-01

An adaptive Genetic Algorithm (GA) is introduced to solve the multi-objective optimized design of the reducer. Firstly, according to the structure, strength, etc. in a reducer, a multi-objective optimized model of the helical gear reducer is established. And then an adaptive GA based on a fuzzy controller is introduced, aiming at the characteristics of multi-objective, multi-parameter, multi-constraint conditions. Finally, a numerical example is illustrated to show the advantages of this approach and the effectiveness of an adaptive genetic algorithm used in optimized design of a reducer.

On the adaptive sliding mode controller for a hyperchaotic fractional-order financial system

NASA Astrophysics Data System (ADS)

Hajipour, Ahamad; Hajipour, Mojtaba; Baleanu, Dumitru

2018-05-01

This manuscript mainly focuses on the construction, dynamic analysis and control of a new fractional-order financial system. The basic dynamical behaviors of the proposed system are studied such as the equilibrium points and their stability, Lyapunov exponents, bifurcation diagrams, phase portraits of state variables and the intervals of system parameters. It is shown that the system exhibits hyperchaotic behavior for a number of system parameters and fractional-order values. To stabilize the proposed hyperchaotic fractional system with uncertain dynamics and disturbances, an efficient adaptive sliding mode controller technique is developed. Using the proposed technique, two hyperchaotic fractional-order financial systems are also synchronized. Numerical simulations are presented to verify the successful performance of the designed controllers.

The company they keep: Background similarity influences transfer of aftereffects from second- to first-order stimuli

PubMed Central

Qian, Ning; Dayan, Peter

2013-01-01

A wealth of studies has found that adapting to second-order visual stimuli has little effect on the perception of first-order stimuli. This is physiologically and psychologically troubling, since many cells show similar tuning to both classes of stimuli, and since adapting to first-order stimuli leads to aftereffects that do generalize to second-order stimuli. Focusing on high-level visual stimuli, we recently proposed the novel explanation that the lack of transfer arises partially from the characteristically different backgrounds of the two stimulus classes. Here, we consider the effect of stimulus backgrounds in the far more prevalent, lower-level, case of the orientation tilt aftereffect. Using a variety of first- and second-order oriented stimuli, we show that we could increase or decrease both within- and cross-class adaptation aftereffects by increasing or decreasing the similarity of the otherwise apparently uninteresting or irrelevant backgrounds of adapting and test patterns. Our results suggest that similarity between background statistics of the adapting and test stimuli contributes to low-level visual adaptation, and that these backgrounds are thus not discarded by visual processing but provide contextual modulation of adaptation. Null cross-adaptation aftereffects must also be interpreted cautiously. These findings reduce the apparent inconsistency between psychophysical and neurophysiological data about first- and second-order stimuli. PMID:23732217

The Neuroanatomical Correlates of Training-Related Perceptuo-Reflex Uncoupling in Dancers

PubMed Central

Nigmatullina, Yuliya; Hellyer, Peter J.; Nachev, Parashkev; Sharp, David J.; Seemungal, Barry M.

2015-01-01

Sensory input evokes low-order reflexes and higher-order perceptual responses. Vestibular stimulation elicits vestibular-ocular reflex (VOR) and self-motion perception (e.g., vertigo) whose response durations are normally equal. Adaptation to repeated whole-body rotations, for example, ballet training, is known to reduce vestibular responses. We investigated the neuroanatomical correlates of vestibular perceptuo-reflex adaptation in ballet dancers and controls. Dancers' vestibular-reflex and perceptual responses to whole-body yaw-plane step rotations were: (1) Briefer and (2) uncorrelated (controls' reflex and perception were correlated). Voxel-based morphometry showed a selective gray matter (GM) reduction in dancers' vestibular cerebellum correlating with ballet experience. Dancers' vestibular cerebellar GM density reduction was related to shorter perceptual responses (i.e. positively correlated) but longer VOR duration (negatively correlated). Contrastingly, controls' vestibular cerebellar GM density negatively correlated with perception and VOR. Diffusion-tensor imaging showed that cerebral cortex white matter (WM) microstructure correlated with vestibular perception but only in controls. In summary, dancers display vestibular perceptuo-reflex dissociation with the neuronatomical correlate localized to the vestibular cerebellum. Controls' robust vestibular perception correlated with a cortical WM network conspicuously absent in dancers. Since primary vestibular afferents synapse in the vestibular cerebellum, we speculate that a cerebellar gating of perceptual signals to cortical regions mediates the training-related attenuation of vestibular perception and perceptuo-reflex uncoupling. PMID:24072889

Adaptive Control of Small Outboard-Powered Boats for Survey Applications

NASA Technical Reports Server (NTRS)

VanZwieten, T.S.; VanZwieten, J.H.; Fisher, A.D.

2009-01-01

Four autopilot controllers have been developed in this work that can both hold a desired heading and follow a straight line. These PID, adaptive PID, neuro-adaptive, and adaptive augmenting control algorithms have all been implemented into a numerical simulation of a 33-foot center console vessel with wind, waves, and current disturbances acting in the perpendicular (across-track) direction of the boat s desired trajectory. Each controller is tested for its ability to follow a desired heading in the presence of these disturbances and then to follow a straight line at two different throttle settings for the same disturbances. These controllers were tuned for an input thrust of 2000 N and all four controllers showed good performance with none of the controllers significantly outperforming the others when holding a constant heading and following a straight line at this engine thrust. Each controller was then tested for a reduced engine thrust of 1200 N per engine where each of the three adaptive controllers reduced heading error and across-track error by approximately 50% after a 300 second tuning period when compared to the fixed gain PID, showing that significant robustness to changes in throttle setting was gained by using an adaptive algorithm.

Adaptive control reduces trip-induced forward gait instability among young adults.

PubMed

Wang, Ting-Yun; Bhatt, Tanvi; Yang, Feng; Pai, Yi-Chung

2012-04-30

A vital functional plasticity of humans is their ability to adapt to threats to posture stability. The purpose of this study was to investigate adaptation to repeated trips in walking. Sixteen young adults were recruited and exposed to the sudden (electronic-mechanical) release of an obstacle, 11-cm in height, in the path of over ground walking during the mid-to-late left swing phase. Although none of the subjects fell on the first of eight unannounced, consecutive trips, all of them had to rely on compensatory step with a step length significantly longer than their regular to reduce their instability. In the subsequent trials, they were able to rapidly make adaptive adjustments in the control of their center-of-mass (COM) stability both proactively and reactively (i.e., before and after hitting or crossing the obstacle), such that the need for taking compensatory step was substantially diminished. The proactive adaptations included a reduced forward COM velocity that lessened forward instability in mid-to-late stance and an elevated toe clearance that reduced the likelihood of obstacle contact. The reactive adjustments were characterized by improved trunk control (by reducing its forward rotation) and limb support (by increasing hip height), and reduced forward instability (by both the posterior COM shift and the reduction in its forward velocity). These findings suggest that young adults can adapt appropriately to repeated trip perturbations and to reduce trip-induced excessive instability in both proactive and reactive manners. Copyright © 2012 Elsevier Ltd. All rights reserved.

A new approach to adaptive control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Issac; Kitsios, Ioannis; Cao, Chengyu; Gregory, Irene M.; Valavani, Lena

2010-01-01

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

On Accuracy of Adaptive Grid Methods for Captured Shocks

NASA Technical Reports Server (NTRS)

Yamaleev, Nail K.; Carpenter, Mark H.

2002-01-01

The accuracy of two grid adaptation strategies, grid redistribution and local grid refinement, is examined by solving the 2-D Euler equations for the supersonic steady flow around a cylinder. Second- and fourth-order linear finite difference shock-capturing schemes, based on the Lax-Friedrichs flux splitting, are used to discretize the governing equations. The grid refinement study shows that for the second-order scheme, neither grid adaptation strategy improves the numerical solution accuracy compared to that calculated on a uniform grid with the same number of grid points. For the fourth-order scheme, the dominant first-order error component is reduced by the grid adaptation, while the design-order error component drastically increases because of the grid nonuniformity. As a result, both grid adaptation techniques improve the numerical solution accuracy only on the coarsest mesh or on very fine grids that are seldom found in practical applications because of the computational cost involved. Similar error behavior has been obtained for the pressure integral across the shock. A simple analysis shows that both grid adaptation strategies are not without penalties in the numerical solution accuracy. Based on these results, a new grid adaptation criterion for captured shocks is proposed.

Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks.

PubMed

Li, Zhijun; Ge, Shuzhi Sam; Liu, Sibang

2014-08-01

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

Flight Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

FPGA-accelerated adaptive optics wavefront control

NASA Astrophysics Data System (ADS)

Mauch, S.; Reger, J.; Reinlein, C.; Appelfelder, M.; Goy, M.; Beckert, E.; Tünnermann, A.

2014-03-01

The speed of real-time adaptive optical systems is primarily restricted by the data processing hardware and computational aspects. Furthermore, the application of mirror layouts with increasing numbers of actuators reduces the bandwidth (speed) of the system and, thus, the number of applicable control algorithms. This burden turns out a key-impediment for deformable mirrors with continuous mirror surface and highly coupled actuator influence functions. In this regard, specialized hardware is necessary for high performance real-time control applications. Our approach to overcome this challenge is an adaptive optics system based on a Shack-Hartmann wavefront sensor (SHWFS) with a CameraLink interface. The data processing is based on a high performance Intel Core i7 Quadcore hard real-time Linux system. Employing a Xilinx Kintex-7 FPGA, an own developed PCie card is outlined in order to accelerate the analysis of a Shack-Hartmann Wavefront Sensor. A recently developed real-time capable spot detection algorithm evaluates the wavefront. The main features of the presented system are the reduction of latency and the acceleration of computation For example, matrix multiplications which in general are of complexity O(n3 are accelerated by using the DSP48 slices of the field-programmable gate array (FPGA) as well as a novel hardware implementation of the SHWFS algorithm. Further benefits are the Streaming SIMD Extensions (SSE) which intensively use the parallelization capability of the processor for further reducing the latency and increasing the bandwidth of the closed-loop. Due to this approach, up to 64 actuators of a deformable mirror can be handled and controlled without noticeable restriction from computational burdens.

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Bayesian selective response-adaptive design using the historical control.

PubMed

Kim, Mi-Ok; Harun, Nusrat; Liu, Chunyan; Khoury, Jane C; Broderick, Joseph P

2018-06-13

High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons, Ltd.

Wavefront sensorless adaptive optics temporal focusing-based multiphoton microscopy

PubMed Central

Chang, Chia-Yuan; Cheng, Li-Chung; Su, Hung-Wei; Hu, Yvonne Yuling; Cho, Keng-Chi; Yen, Wei-Chung; Xu, Chris; Dong, Chen Yuan; Chen, Shean-Jen

2014-01-01

Temporal profile distortions reduce excitation efficiency and image quality in temporal focusing-based multiphoton microscopy. In order to compensate the distortions, a wavefront sensorless adaptive optics system (AOS) was integrated into the microscope. The feedback control signal of the AOS was acquired from local image intensity maximization via a hill-climbing algorithm. The control signal was then utilized to drive a deformable mirror in such a way as to eliminate the distortions. With the AOS correction, not only is the axial excitation symmetrically refocused, but the axial resolution with full two-photon excited fluorescence (TPEF) intensity is also maintained. Hence, the contrast of the TPEF image of a R6G-doped PMMA thin film is enhanced along with a 3.7-fold increase in intensity. Furthermore, the TPEF image quality of 1μm fluorescent beads sealed in agarose gel at different depths is improved. PMID:24940539

Public Health and Climate Change Adaptation at the Federal Level: One Agency’s Response to Executive Order 13514

PubMed Central

Schramm, Paul J.; Luber, George

2014-01-01

Climate change will likely have adverse human health effects that require federal agency involvement in adaptation activities. In 2009, President Obama issued Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance. The order required federal agencies to develop and implement climate change adaptation plans. The Centers for Disease Control and Prevention (CDC), as part of a larger Department of Health and Human Services response to climate change, is developing such plans. We provide background on Executive Orders, outline tenets of climate change adaptation, discuss public health adaptation planning at both the Department of Health and Human Services and the CDC, and outline possible future CDC efforts. We also consider how these activities may be better integrated with other adaptation activities that manage emerging health threats posed by climate change. PMID:24432931

Public health and climate change adaptation at the federal level: one agency's response to Executive Order 13514.

PubMed

Hess, Jeremy J; Schramm, Paul J; Luber, George

2014-03-01

Climate change will likely have adverse human health effects that require federal agency involvement in adaptation activities. In 2009, President Obama issued Executive Order 13514, Federal Leadership in Environmental, Energy, and Economic Performance. The order required federal agencies to develop and implement climate change adaptation plans. The Centers for Disease Control and Prevention (CDC), as part of a larger Department of Health and Human Services response to climate change, is developing such plans. We provide background on Executive Orders, outline tenets of climate change adaptation, discuss public health adaptation planning at both the Department of Health and Human Services and the CDC, and outline possible future CDC efforts. We also consider how these activities may be better integrated with other adaptation activities that manage emerging health threats posed by climate change.

Adaptive Fuzzy Hysteresis Band Current Controller for Four-Wire Shunt Active Filter

NASA Astrophysics Data System (ADS)

Hamoudi, F.; Chaghi, A.; Amimeur, H.; Merabet, E.

2008-06-01

This paper presents an adaptive fuzzy hysteresis band current controller for four-wire shunt active power filters to eliminate harmonics and to compensate reactive power in distribution systems in order to keep currents at the point of common coupling sinusoidal and in phase with the corresponding voltage and the cancel neutral current. The conventional hysteresis band known for its robustness and its advantage in current controlled applications is adapted with a fuzzy logic controller to change the bandwidth according to the operating point in order to keep the frequency modulation at tolerable limits. The algorithm used to identify the reference currents is based on the synchronous reference frame theory (dqγ). Finally, simulation results using Matlab/Simulink are given to validate the proposed control.

Simplified adaptive control of an orbiting flexible spacecraft

NASA Astrophysics Data System (ADS)

Maganti, Ganesh B.; Singh, Sahjendra N.

2007-10-01

The paper presents the design of a new simple adaptive system for the rotational maneuver and vibration suppression of an orbiting spacecraft with flexible appendages. A moment generating device located on the central rigid body of the spacecraft is used for the attitude control. It is assumed that the system parameters are unknown and the truncated model of the spacecraft has finite but arbitrary dimension. In addition, only the pitch angle and its derivative are measured and elastic modes are not available for feedback. The control output variable is chosen as the linear combination of the pitch angle and the pitch rate. Exploiting the hyper minimum phase nature of the spacecraft, a simple adaptive control law is derived for the pitch angle control and elastic mode stabilization. The adaptation rule requires only four adjustable parameters and the structure of the control system does not depend on the order of the truncated spacecraft model. For the synthesis of control system, the measured output error and the states of a third-order command generator are used. Simulation results are presented which show that in the closed-loop system adaptive output regulation is accomplished in spite of large parameter uncertainties and disturbance input.

Robust Optimal Adaptive Control Method with Large Adaptive Gain

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Wire rope tension control of hoisting systems using a robust nonlinear adaptive backstepping control scheme.

PubMed

Zhu, Zhen-Cai; Li, Xiang; Shen, Gang; Zhu, Wei-Dong

2018-01-01

This paper concerns wire rope tension control of a double-rope winding hoisting system (DRWHS), which consists of a hoisting system employed to realize a transportation function and an electro-hydraulic servo system utilized to adjust wire rope tensions. A dynamic model of the DRWHS is developed in which parameter uncertainties and external disturbances are considered. A comparison between simulation results using the dynamic model and experimental results using a double-rope winding hoisting experimental system is given in order to demonstrate accuracy of the dynamic model. In order to improve the wire rope tension coordination control performance of the DRWHS, a robust nonlinear adaptive backstepping controller (RNABC) combined with a nonlinear disturbance observer (NDO) is proposed. Main features of the proposed combined controller are: (1) using the RNABC to adjust wire rope tensions with consideration of parameter uncertainties, whose parameters are designed online by adaptive laws derived from Lyapunov stability theory to guarantee the control performance and stability of the closed-loop system; and (2) introducing the NDO to deal with uncertain external disturbances. In order to demonstrate feasibility and effectiveness of the proposed controller, experimental studies have been conducted on the DRWHS controlled by an xPC rapid prototyping system. Experimental results verify that the proposed controller exhibits excellent performance on wire rope tension coordination control compared with a conventional proportional-integral (PI) controller and adaptive backstepping controller. Copyright © 2017 ISA. All rights reserved.

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens.

PubMed

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N; Zawadzki, Robert J; Sarunic, Marinko V

2015-08-24

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images.

Adaptive Fractional-order Control for Synchronization of Two Coupled Neurons in the External Electrical Stimulation

PubMed Central

Mehdiabadi, M. R. Rahmani; Rouhani, E.; Mashhadi, S. K. Mousavi; Jalali, A. A.

2014-01-01

This paper addresses synchronizing two coupled chaotic FitzHugh–Nagumo (FHN) neurons with weakly gap junction under external electrical stimulation (EES). To transmit information among coupled neurons, by generalization of the integer-order FHN equations of the coupled system into the fractional-order in frequency domain using Crone approach, the behavior of each coupled neuron relies on its past behavior and the memorized system can be a better fit for the neuron response. An adaptive fractional-order controller based on the Lyaponuv stability theory was designed to synchronize two neurons electrically coupled with gap junction in EES. The proposed controller is also robust to the inevitable random noise such as disturbances of ionic channels. The simulation results demonstrate the effectiveness of the control scheme. PMID:25337373

Recurrent myocardial infarction: Mechanisms of free-floating adaptation and autonomic derangement in networked cardiac neural control

PubMed Central

Ardell, Jeffrey L.; Shivkumar, Kalyanam; Armour, J. Andrew

2017-01-01

The cardiac nervous system continuously controls cardiac function whether or not pathology is present. While myocardial infarction typically has a major and catastrophic impact, population studies have shown that longer-term risk for recurrent myocardial infarction and the related potential for sudden cardiac death depends mainly upon standard atherosclerotic variables and autonomic nervous system maladaptations. Investigative neurocardiology has demonstrated that autonomic control of cardiac function includes local circuit neurons for networked control within the peripheral nervous system. The structural and adaptive characteristics of such networked interactions define the dynamics and a new normal for cardiac control that results in the aftermath of recurrent myocardial infarction and/or unstable angina that may or may not precipitate autonomic derangement. These features are explored here via a mathematical model of cardiac regulation. A main observation is that the control environment during pathology is an extrapolation to a setting outside prior experience. Although global bounds guarantee stability, the resulting closed-loop dynamics exhibited while the network adapts during pathology are aptly described as ‘free-floating’ in order to emphasize their dependence upon details of the network structure. The totality of the results provide a mechanistic reasoning that validates the clinical practice of reducing sympathetic efferent neuronal tone while aggressively targeting autonomic derangement in the treatment of ischemic heart disease. PMID:28692680

An energy-efficient rate adaptive media access protocol (RA-MAC) for long-lived sensor networks.

PubMed

Hu, Wen; Chen, Quanjun; Corke, Peter; O'Rourke, Damien

2010-01-01

We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC) algorithm for long-lived Wireless Sensor Networks (WSNs). Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application's link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode) on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment.

Nonlinear adaptive inverse control via the unified model neural network

NASA Astrophysics Data System (ADS)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Unconsciously triggered conflict adaptation.

PubMed

van Gaal, Simon; Lamme, Victor A F; Ridderinkhof, K Richard

2010-07-09

In conflict tasks such as the Stroop, the Eriksen flanker or the Simon task, it is generally observed that the detection of conflict in the current trial reduces the impact of conflicting information in the subsequent trial; a phenomenon termed conflict adaptation. This higher-order cognitive control function has been assumed to be restricted to cases where conflict is experienced consciously. In the present experiment we manipulated the awareness of conflict-inducing stimuli in a metacontrast masking paradigm to directly test this assumption. Conflicting response tendencies were elicited either consciously (through primes that were weakly masked) or unconsciously (strongly masked primes). We demonstrate trial-by-trial conflict adaptation effects after conscious as well as unconscious conflict, which could not be explained by direct stimulus/response repetitions. These findings show that unconscious information can have a longer-lasting influence on our behavior than previously thought and further stretch the functional boundaries of unconscious cognition.

Unconsciously Triggered Conflict Adaptation

PubMed Central

van Gaal, Simon; Lamme, Victor A. F.; Ridderinkhof, K. Richard

2010-01-01

In conflict tasks such as the Stroop, the Eriksen flanker or the Simon task, it is generally observed that the detection of conflict in the current trial reduces the impact of conflicting information in the subsequent trial; a phenomenon termed conflict adaptation. This higher-order cognitive control function has been assumed to be restricted to cases where conflict is experienced consciously. In the present experiment we manipulated the awareness of conflict-inducing stimuli in a metacontrast masking paradigm to directly test this assumption. Conflicting response tendencies were elicited either consciously (through primes that were weakly masked) or unconsciously (strongly masked primes). We demonstrate trial-by-trial conflict adaptation effects after conscious as well as unconscious conflict, which could not be explained by direct stimulus/response repetitions. These findings show that unconscious information can have a longer-lasting influence on our behavior than previously thought and further stretch the functional boundaries of unconscious cognition. PMID:20634898

Active Control of High Frequency Combustion Instability in Aircraft Gas-Turbine Engines

NASA Technical Reports Server (NTRS)

Corrigan, Bob (Technical Monitor); DeLaat, John C.; Chang, Clarence T.

2003-01-01

Active control of high-frequency (greater than 500 Hz) combustion instability has been demonstrated in the NASA single-nozzle combustor rig at United Technologies Research Center. The combustor rig emulates an actual engine instability and has many of the complexities of a real engine combustor (i.e. actual fuel nozzle and swirler, dilution cooling, etc.) In order to demonstrate control, a high-frequency fuel valve capable of modulating the fuel flow at up to 1kHz was developed. Characterization of the fuel delivery system was accomplished in a custom dynamic flow rig developed for that purpose. Two instability control methods, one model-based and one based on adaptive phase-shifting, were developed and evaluated against reduced order models and a Sectored-1-dimensional model of the combustor rig. Open-loop fuel modulation testing in the rig demonstrated sufficient fuel modulation authority to proceed with closed-loop testing. During closed-loop testing, both control methods were able to identify the instability from the background noise and were shown to reduce the pressure oscillations at the instability frequency by 30%. This is the first known successful demonstration of high-frequency combustion instability suppression in a realistic aero-engine environment. Future plans are to carry these technologies forward to demonstration on an advanced low-emission combustor.

Resting State Synchrony in Short-Term versus Long-Term Abstinent Alcoholics

PubMed Central

Camchong, Jazmin; Stenger, Victor Andrew; Fein, George

2012-01-01

BACKGROUND We previously reported that when compared to controls, long-term abstinent alcoholics (LTAA) have increased resting state synchrony (RSS) of the inhibitory control network and reduced synchrony of the appetitive drive network, and hypothesized that these levels of synchrony are adaptive, and support the behavioral changes required to maintain abstinence. In the current study, we investigate whether these RSS patterns can be identified in short-term abstinent alcoholics. METHODS Resting state functional magnetic resonance imaging data were collected from 27 short-term abstinent alcoholics (STAA), 23 LTAA and 23 non-substance abusing controls (NSAC). We examined baseline RSS using seed-based measures. RESULTS We found ordered RSS effects from NSAC to STAA and then to LTAA within both the appetitive drive and executive control networks: increasing RSS of the executive control network, and decreasing RSS of the reward processing network. Finally, we found significant correlations between strength of RSS in these networks and (a) cognitive flexibility and (b) current antisocial behavior. DISCUSSION Findings are consistent with an adaptive progression of RSS from short- to long-term abstinence so that, compared to normal controls, the synchrony (a) within the reward network progressively decreases and (b) within the executive control network progressively increases. PMID:23421812

Initial results from the Lick Observatory Laser Guide Star Adaptive Optics System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olivier, S.S.; An, J.; Avicola, K.

1995-11-08

A prototype adaptive optics system has been installed and tested on the 3 m Shane telescope at Lick Observatory. The adaptive optics system performance, using bright natural guide stars, is consistent with expectations based on theory. A sodium-layer laser guide star system has also been installed and tested on the Shane telescope. Operating at 15 W, the laser system produces a 9th magnitude guide star with seeing-limited size at 589 nm. Using the laser guide star, the adaptive optics system has reduced the wavefront phase variance on scales above 50 cm by a factor of 4. These results represent themore » first continuous wavefront phase correction using a sodium-layer laser guide star. Assuming tip-tilt is removed using a natural guide star, the measured control loop performance should produce images with a Strehl ratio of 0.4 at 2.2 {mu}m in 1 arc second seeing. Additional calibration procedures must be implemented in order to achieve these results with the prototype Lick adaptive optics system.« less

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

NASA Technical Reports Server (NTRS)

Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

2013-01-01

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Innate control of adaptive immunity: Beyond the three-signal paradigm

PubMed Central

Jain, Aakanksha; Pasare, Chandrashekhar

2017-01-01

Activation of cells in the adaptive immune system is a highly orchestrated process dictated by multiples cues from the innate immune system. Although the fundamental principles of innate control of adaptive immunity are well established, it is not fully understood how innate cells integrate qualitative pathogenic information in order to generate tailored protective adaptive immune responses. In this review, we discuss complexities involved in the innate control of adaptive immunity that extend beyond T cell receptor engagement, co-stimulation and priming cytokine production but are critical for generation of protective T cell immunity. PMID:28483987

Augmented Adaptive Control of a Wind Turbine in the Presence of Structural Modes

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.; Wright, Alan D.

2010-01-01

Wind turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, potentially causing component fatigue and failure. Two key technology drivers for turbine manufacturers are increasing turbine up time and reducing maintenance costs. Since the trend in wind turbine design is towards larger, more flexible turbines with lower frequency structural modes, manufacturers will want to develop methods to operate in the presence of these modes. Accurate models of the dynamic characteristics of new wind turbines are often not available due to the complexity and expense of the modeling task, making wind turbines ideally suited to adaptive control. In this paper, we develop theory for adaptive control with rejection of disturbances in the presence of modes that inhibit the controller. We use this method to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the interference of certain structural modes in feedback. The control objective is accomplished by collectively pitching the turbine blades. The adaptive pitch controller for Region 3 is compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller.

Efficacy of Coming Out Proud to reduce stigma’s impact among people with mental illness: pilot randomised controlled trial

PubMed Central

Rüsch, Nicolas; Abbruzzese, Elvira; Hagedorn, Eva; Hartenhauer, Daniel; Kaufmann, Ilias; Curschellas, Jan; Ventling, Stephanie; Zuaboni, Gianfranco; Bridler, René; Olschewski, Manfred; Kawohl, Wolfram; Rössler, Wulf; Kleim, Birgit; Corrigan, Patrick W.

2014-01-01

Background Facing frequent stigma and discrimination, many people with mental illness have to choose between secrecy and disclosure in different settings. Coming Out Proud (COP), a 3-week peer-led group intervention, offers support in this domain in order to reduce stigma’s negative impact. Aims To examine COP’s efficacy to reduce negative stigma-related outcomes and to promote adaptive coping styles (Current Controlled Trials number: ISRCTN43516734). Method In a pilot randomised controlled trial, 100 participants with mental illness were assigned to COP or a treatment-as-usual control condition. Outcomes included self-stigma, empowerment, stigma stress, secrecy and perceived benefits of disclosure. Results Intention-to-treat analyses found no effect of COP on self-stigma or empowerment, but positive effects on stigma stress, disclosure-related distress, secrecy and perceived benefits of disclosure. Some effects diminished during the 3-week follow-up period. Conclusions Coming Out Proud has immediate positive effects on disclosure- and stigma stress-related variables and may thus alleviate stigma’s negative impact. PMID:24434073

IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

NASA Astrophysics Data System (ADS)

Boz, Utku; Basdogan, Ipek

2015-12-01

Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

A Phase-Shifting Zernike Wavefront Sensor for the Palomar P3K Adaptive Optics System

NASA Technical Reports Server (NTRS)

Wallace, J. Kent; Crawford, Sam; Loya, Frank; Moore, James

2012-01-01

A phase-shifting Zernike wavefront sensor has distinct advantages over other types of wavefront sensors. Chief among them are: 1) improved sensitivity to low-order aberrations and 2) efficient use of photons (hence reduced sensitivity to photon noise). We are in the process of deploying a phase-shifting Zernike wavefront sensor to be used with the realtime adaptive optics system for Palomar. Here we present the current state of the Zernike wavefront sensor to be integrated into the high-order adaptive optics system at Mount Palomar's Hale Telescope.

Climate change and health: impacts, vulnerability, adaptation and mitigation.

PubMed

Kjellstrom, Tord; Weaver, Haylee J

2009-01-01

Global climate change is progressing and health impacts have been observed in a number of countries, including Australia. The main health impacts will be due to direct heat exposure, extreme weather, air pollution, reduced local food production, food- and vectorborne infectious diseases and mental stress. The issue is one of major public health importance. Adaptation to reduce the effects of climate change involves many different sectors to minimise negative health outcomes. Wide-scale mitigation is also required, in order to reduce the effects of climate change. In addition, future urban design must be modified to mitigate and adapt to the effects of climate change. Strategies for mitigation and adaptation can create co-benefits for both individual and community health, by reducing non-climate-related health hazard exposures and by encouraging health promoting behaviours and lifestyles.

Reduced-order modeling for hyperthermia control.

PubMed

Potocki, J K; Tharp, H S

1992-12-01

This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS). These thermal state space models are reduced using the balanced realization technique, and an order reduction criterion is tabulated. Results show that a drastic reduction in model dimension can be achieved using the balanced realization. The reduced-order model is then used to design a reduced-order optimal servomechanism controller for a two-scan input, two thermocouple output tissue model. In addition, a full-order optimal servomechanism controller is designed for comparison and validation purposes. These two controllers are applied to a variety of perturbed tissue thermal models to test the robust nature of the reduced-order controller. A comparison of the two controllers validates the use of open-loop balanced reduced-order models in the design of MIMO hyperthermia controllers.

Cascade and parallel combination (CPC) of adaptive filters for estimating heart rate during intensive physical exercise from photoplethysmographic signal

PubMed Central

Islam, Mohammad Tariqul; Tanvir Ahmed, Sk.; Zabir, Ishmam; Shahnaz, Celia

2018-01-01

Photoplethysmographic (PPG) signal is getting popularity for monitoring heart rate in wearable devices because of simplicity of construction and low cost of the sensor. The task becomes very difficult due to the presence of various motion artefacts. In this study, an algorithm based on cascade and parallel combination (CPC) of adaptive filters is proposed in order to reduce the effect of motion artefacts. First, preliminary noise reduction is performed by averaging two channel PPG signals. Next in order to reduce the effect of motion artefacts, a cascaded filter structure consisting of three cascaded adaptive filter blocks is developed where three-channel accelerometer signals are used as references to motion artefacts. To further reduce the affect of noise, a scheme based on convex combination of two such cascaded adaptive noise cancelers is introduced, where two widely used adaptive filters namely recursive least squares and least mean squares filters are employed. Heart rates are estimated from the noise reduced PPG signal in spectral domain. Finally, an efficient heart rate tracking algorithm is designed based on the nature of the heart rate variability. The performance of the proposed CPC method is tested on a widely used public database. It is found that the proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach. PMID:29515812

Spacecraft Maneuvering at the Sun/Earth-Moon L2 Libration Point

NASA Astrophysics Data System (ADS)

Shahid, Kamran

Spacecraft formation flying in the vicinity of the Sun/Earth-Moon libration points offers many promising possibilities for space exploration. The concept of formation flying involves the distribution of the functionality of a single spacecraft among several smaller, cooperative spacecraft. The libration points are locations relative to two large orbiting bodies where a third body with relatively small mass can remain stationary relative to the two larger bodies. The most significant perturbation experienced by a spacecraft at the libration point is effect of solar radiation pressure. This thesis presents the development of nonlinear control techniques for maneuvering control at the Sun-Earth/Moon L2 libration point. A new thruster based formation control technique is presented. We also consider a leader/follower formation architecture, and examine the station keeping control of the leader spacecraft and the formation control of the follower spacecraft using solar radiation pressure. Reference trajectories of the leader spacecraft, halo and Lissajous orbits, are determined using a numerical technique in order to take into account all major gravitational perturbations. The nonlinear controllers are developed based on Lyapunov analysis, including non-adaptive and adaptive designs. Thruster based and solar radiation pressure based control laws for spacecraft maneuvering at the Sun-Earth/Moon libration point are developed. Higher order sliding mode control is utilized to address the non-affine structure of the solar sail control inputs. The reduced input solar radiation pressure problem is properly addressed as an underactuated control problem. The development of adaptive control for solar sail equipped spacecraft is an innovation and represents and advancement in solar sailing control technology. Controller performance is evaluated in a high fidelity ephemeris model to reflect a realistic simulated space environment. The numerical results demonstrate the effectiveness of the proposed control techniques for spacecraft maneuvering using solar radiation pressure at the L2 libration point. Stationkeeping accuracies of 50m and formation maintenance accuracies of less than 1m are possible using solar radiation pressure at a sub-L2 libration point. The benefits of these control techniques include increasing libration point mission lifetimes and doubling payload mass fractions as compared to conventional propulsion methods.

Family Adaptation and Coping among Siblings of Cancer Patients, Their Brothers and Sisters, and Nonclinical Controls.

ERIC Educational Resources Information Center

Madan-Swain, Avi; And Others

1993-01-01

Examined coping and family adaptation in siblings (n=32) of cancer patients, their ill brothers and sisters (n=19), and control group of nonclinical children (n=10) with healthy siblings. Gender and age of sibling, birth order, and number of siblings were examined. Found better adaptation in larger families and decreased family involvement among…

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

NASA Technical Reports Server (NTRS)

Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

2010-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Extended observer based on adaptive second order sliding mode control for a fixed wing UAV.

PubMed

Castañeda, Herman; Salas-Peña, Oscar S; León-Morales, Jesús de

2017-01-01

This paper addresses the design of attitude and airspeed controllers for a fixed wing unmanned aerial vehicle. An adaptive second order sliding mode control is proposed for improving performance under different operating conditions and is robust in presence of external disturbances. Moreover, this control does not require the knowledge of disturbance bounds and avoids overestimation of the control gains. Furthermore, in order to implement this controller, an extended observer is designed to estimate unmeasurable states as well as external disturbances. Additionally, sufficient conditions are given to guarantee the closed-loop stability of the observer based control. Finally, using a full 6 degree of freedom model, simulation results are obtained where the performance of the proposed method is compared against active disturbance rejection based on sliding mode control. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Tian, Mingyan; Huang, Jiaqi; Zhang, Rui; Ma, Zhen

2015-09-01

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

hp-Adaptive time integration based on the BDF for viscous flows

NASA Astrophysics Data System (ADS)

Hay, A.; Etienne, S.; Pelletier, D.; Garon, A.

2015-06-01

This paper presents a procedure based on the Backward Differentiation Formulas of order 1 to 5 to obtain efficient time integration of the incompressible Navier-Stokes equations. The adaptive algorithm performs both stepsize and order selections to control respectively the solution accuracy and the computational efficiency of the time integration process. The stepsize selection (h-adaptivity) is based on a local error estimate and an error controller to guarantee that the numerical solution accuracy is within a user prescribed tolerance. The order selection (p-adaptivity) relies on the idea that low-accuracy solutions can be computed efficiently by low order time integrators while accurate solutions require high order time integrators to keep computational time low. The selection is based on a stability test that detects growing numerical noise and deems a method of order p stable if there is no method of lower order that delivers the same solution accuracy for a larger stepsize. Hence, it guarantees both that (1) the used method of integration operates inside of its stability region and (2) the time integration procedure is computationally efficient. The proposed time integration procedure also features a time-step rejection and quarantine mechanisms, a modified Newton method with a predictor and dense output techniques to compute solution at off-step points.

Adaptive neural network backstepping control for a class of uncertain fractional-order chaotic systems with unknown backlash-like hysteresis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Yimin; Lv, Hui, E-mail: lvhui207@gmail.com

In this paper, we consider the control problem of a class of uncertain fractional-order chaotic systems preceded by unknown backlash-like hysteresis nonlinearities based on backstepping control algorithm. We model the hysteresis by using a differential equation. Based on the fractional Lyapunov stability criterion and the backstepping algorithm procedures, an adaptive neural network controller is driven. No knowledge of the upper bound of the disturbance and system uncertainty is required in our controller, and the asymptotical convergence of the tracking error can be guaranteed. Finally, we give two simulation examples to confirm our theoretical results.

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens

PubMed Central

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N.; Zawadzki, Robert J.; Sarunic, Marinko V.

2015-01-01

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images. PMID:26368169

Application of model reference adaptive control to a flexible remote manipulator arm

NASA Technical Reports Server (NTRS)

Meldrum, D. R.; Balas, M. J.

1986-01-01

An exact modal state-space representation is derived in detail for a single-link, flexible remote manipulator with a noncollocated sensor and actuator. A direct model following adaptive controller is designed to control the torque at the pinned end of the arm so as to command the free end to track a prescribed sinusoidal motion. Conditions that must be satisfied in order for the controller to work are stated. Simulation results to date are discussed along with the potential of the model following adaptive control scheme in robotics and space environments.

An Efficient Adaptive Angle-Doppler Compensation Approach for Non-Sidelooking Airborne Radar STAP

PubMed Central

Shen, Mingwei; Yu, Jia; Wu, Di; Zhu, Daiyin

2015-01-01

In this study, the effects of non-sidelooking airborne radar clutter dispersion on space-time adaptive processing (STAP) is considered, and an efficient adaptive angle-Doppler compensation (EAADC) approach is proposed to improve the clutter suppression performance. In order to reduce the computational complexity, the reduced-dimension sparse reconstruction (RDSR) technique is introduced into the angle-Doppler spectrum estimation to extract the required parameters for compensating the clutter spectral center misalignment. Simulation results to demonstrate the effectiveness of the proposed algorithm are presented. PMID:26053755

Cooperative Adaptive Cruise Control Human Factors Study : Experiment 1 - Workload, Distraction, Arousal, and Trust

DOT National Transportation Integrated Search

2016-12-01

This study set out to examine the following diverse questions regarding cooperative adaptive cruise control (CACC) use: - Does CACC reduce driver workload relative to manual gap control? - Does CACC increase the probability of driver distraction rela...

An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems

NASA Astrophysics Data System (ADS)

Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.

2016-04-01

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).

Design of modular control system for grain dryers

NASA Astrophysics Data System (ADS)

He, Gaoqing; Liu, Yanhua; Zu, Yuan

In order to effectively control the temperature of grain drying bin, grain ,air outlet as well as the grain moisture, it designed the control system of 5HCY-35 which is based on MCU to adapt to all grains drying conditions, high drying efficiency, long life usage and less manually. The system includes: the control module of the constant temperature and the temperature difference control in drying bin, the constant temperature control of heating furnace, on-line testing of moisture, variety of grain-circulation speed control and human-computer interaction interface. Spatial curve simulation, which takes moisture as control objectives, controls the constant temperature and the temperature difference in drying bin according to preset parameter by the user or a list to reduce the grains explosive to ensure the seed germination percentage. The system can realize the intelligent control of high efficiency and various drying, the good scalability and the high quality.

ENDURANCE TRAINING IN FASTING CONDITIONS: BIOLOGICAL ADAPTATIONS AND BODY WEIGHT MANAGEMENT.

PubMed

Vicente-Salar, Néstor; Urdampilleta Otegui, Aritz; Roche Collado, Enrique

2015-12-01

in the majority of sports the athlete is required to achieve optimal conditions both at a muscular and metabolic level as well as in body composition, increasing the lean body mass and maintaining a low body fat mass. In this context, different training protocols have been proposed in order to reduce body fat content, by maximizing fat use instead of glycogen. to verify if the training while fasting favours the use of fatty acids due to the low glycogen levels, allowing an improvement in the performance ant the control of body weight. protocols have been published, differing in time periods and exercise intensity. In addition, several markers ranging from gene expression analysis to determination of circulating parameters have been assessed in order to interpret the results. Discusion: at low intensities of endurance-based exercises, adipose tissue lipolysis and muscle fat oxidation rate seem to be higher in fasting than in fed state. On the other hand, glucose metabolism is adapted in order to save glycogen stores, possibly through gluconeogenesis activation. Finally, it has been observed that protein degradation is mainly downregulated. Only one study analyses changes in body composition after fasting during long periods, thus further work is necessary to demonstrate that this is the best method to control body fat. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Fast spacecraft adaptive attitude tracking control through immersion and invariance design

NASA Astrophysics Data System (ADS)

Wen, Haowei; Yue, Xiaokui; Li, Peng; Yuan, Jianping

2017-10-01

This paper presents a novel non-certainty-equivalence adaptive control method for the attitude tracking control problem of spacecraft with inertia uncertainties. The proposed immersion and invariance (I&I) based adaptation law provides a more direct and flexible approach to circumvent the limitations of the basic I&I method without employing any filter signal. By virtue of the adaptation high-gain equivalence property derived from the proposed adaptive method, the closed-loop adaptive system with a low adaptation gain could recover the high adaptation gain performance of the filter-based I&I method, and the resulting control torque demands during the initial transient has been significantly reduced. A special feature of this method is that the convergence of the parameter estimation error has been observably improved by utilizing an adaptation gain matrix instead of a single adaptation gain value. Numerical simulations are presented to highlight the various benefits of the proposed method compared with the certainty-equivalence-based control method and filter-based I&I control schemes.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems.

PubMed

Ashtiani Haghighi, Donya; Mobayen, Saleh

2018-04-01

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive weld control for high-integrity welding applications

NASA Technical Reports Server (NTRS)

Powell, Bradley W.

1993-01-01

An advanced adaptive control weld system for high-integrity welding applications is presented. The system consists of a state-of-the-art weld control subsystem, motion control subsystem, and sensor subsystem which closes the loop on the process. The adaptive control subsystem (ACS), which is required to totally close the loop on weld process control, consists of a multiprocessor system, data acquisition hardware, and three welding sensors which provide measurements from all areas around the torch in real time. The ACS acquires all 'measurables' and feeds offset trims back into the weld control and motion control subsystems to modify the 'controllables' in order to maintain a previously defined weld quality.

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

PubMed

Liu, Quan; Liu, Aiming; Meng, Wei; Ai, Qingsong; Xie, Sheng Q

2017-01-01

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient's active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant's assessment. The robot reduces its assistance output when participants contribute more and vice versa , thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

PubMed Central

Liu, Quan; Liu, Aiming; Meng, Wei; Ai, Qingsong; Xie, Sheng Q.

2017-01-01

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient’s active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant’s assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy. PMID:29255412

Hysteresis compensation of piezoelectric deformable mirror based on Prandtl-Ishlinskii model

NASA Astrophysics Data System (ADS)

Ma, Jianqiang; Tian, Lei; Li, Yan; Yang, Zongfeng; Cui, Yuguo; Chu, Jiaru

2018-06-01

Hysteresis of piezoelectric deformable mirror (DM) reduces the closed-loop bandwidth and the open-loop correction accuracy of adaptive optics (AO) systems. In this work, a classical Prandtl-Ishlinskii (PI) model is employed to model the hysteresis behavior of a unimorph DM with 20 actuators. A modified control algorithm combined with the inverse PI model is developed for piezoelectric DMs. With the help of PI model, the hysteresis of the DM was reduced effectively from about 9% to 1%. Furthermore, open-loop regenerations of low-order aberrations with or without hysteresis compensation were carried out. The experimental results demonstrate that the regeneration accuracy with PI model compensation is significantly improved.

Model predictive control based on reduced order models applied to belt conveyor system.

PubMed

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear discrete-time multirate adaptive control of non-linear vibrations of smart beams

NASA Astrophysics Data System (ADS)

Georgiou, Georgios; Foutsitzi, Georgia A.; Stavroulakis, Georgios E.

2018-06-01

The nonlinear adaptive digital control of a smart piezoelectric beam is considered. It is shown that in the case of a sampled-data context, a multirate control strategy provides an appropriate framework in order to achieve vibration regulation, ensuring the stability of the whole control system. Under parametric uncertainties in the model parameters (damping ratios, frequencies, levels of non linearities and cross coupling, control input parameters), the scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sampling instants. Simulation results are presented.

The adaptive observer. [liapunov synthesis, single-input single-output, and reduced observers

NASA Technical Reports Server (NTRS)

Carroll, R. L.

1973-01-01

The simple generation of state from available measurements, for use in systems for which the criteria defining the acceptable state behavior mandates a control that is dependent upon unavailable measurement is described as an adaptive means for determining the state of a linear time invariant differential system having unknown parameters. A single input output adaptive observer and the reduced adaptive observer is developed. The basic ideas for both the adaptive observer and the nonadaptive observer are examined. A survey of the Liapunov synthesis technique is taken, and the technique is applied to adaptive algorithm for the adaptive observer.

Effects of incomplete adaption and disturbance in adaptive control

NASA Technical Reports Server (NTRS)

Lindorff, D. P.

1972-01-01

This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.

Transient analysis of an adaptive system for optimization of design parameters

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

Averaging methods are applied to analyzing and optimizing the transient response associated with the direct adaptive control of an oscillatory second-order minimum-phase system. The analytical design methods developed for a second-order plant can be applied with some approximation to a MIMO flexible structure having a single dominant mode.

Controller reduction by preserving impulse response energy

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.; Su, Tzu-Jeng

1989-01-01

A model order reduction algorithm based on a Krylov recurrence formulation is developed to reduce order of controllers. The reduced-order controller is obtained by projecting the full-order LQG controller onto a Krylov subspace in which either the controllability or the observability grammian is equal to the identity matrix. The reduced-order controller preserves the impulse response energy of the full-order controller and has a parameter-matching property. Two numerical examples drawn from other controller reduction literature are used to illustrate the efficacy of the proposed reduction algorithm.

Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system

NASA Astrophysics Data System (ADS)

Yang, Yana; Hua, Changchun; Li, Junpeng; Guan, Xinping

2017-12-01

This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler-Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.

Development of a Design Methodology for Reconfigurable Flight Control Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; McLean, C.

2000-01-01

A methodology is presented for the design of flight control systems that exhibit stability and performance-robustness in the presence of actuator failures. The design is based upon two elements. The first element consists of a control law that will ensure at least stability in the presence of a class of actuator failures. This law is created by inner-loop, reduced-order, linear dynamic inversion, and outer-loop compensation based upon Quantitative Feedback Theory. The second element consists of adaptive compensators obtained from simple and approximate time-domain identification of the dynamics of the 'effective vehicle' with failed actuator(s). An example involving the lateral-directional control of a fighter aircraft is employed both to introduce the proposed methodology and to demonstrate its effectiveness and limitations.

Fast calibration of high-order adaptive optics systems.

PubMed

Kasper, Markus; Fedrigo, Enrico; Looze, Douglas P; Bonnet, Henri; Ivanescu, Liviu; Oberti, Sylvain

2004-06-01

We present a new method of calibrating adaptive optics systems that greatly reduces the required calibration time or, equivalently, improves the signal-to-noise ratio. The method uses an optimized actuation scheme with Hadamard patterns and does not scale with the number of actuators for a given noise level in the wavefront sensor channels. It is therefore highly desirable for high-order systems and/or adaptive secondary systems on a telescope without a Gregorian focal plane. In the latter case, the measurement noise is increased by the effects of the turbulent atmosphere when one is calibrating on a natural guide star.

Quick-low-density parity check and dynamic threshold voltage optimization in 1X nm triple-level cell NAND flash memory with comprehensive analysis of endurance, retention-time, and temperature variation

NASA Astrophysics Data System (ADS)

Doi, Masafumi; Tokutomi, Tsukasa; Hachiya, Shogo; Kobayashi, Atsuro; Tanakamaru, Shuhei; Ning, Sheyang; Ogura Iwasaki, Tomoko; Takeuchi, Ken

2016-08-01

NAND flash memory’s reliability degrades with increasing endurance, retention-time and/or temperature. After a comprehensive evaluation of 1X nm triple-level cell (TLC) NAND flash, two highly reliable techniques are proposed. The first proposal, quick low-density parity check (Quick-LDPC), requires only one cell read in order to accurately estimate a bit-error rate (BER) that includes the effects of temperature, write and erase (W/E) cycles and retention-time. As a result, 83% read latency reduction is achieved compared to conventional AEP-LDPC. Also, W/E cycling is extended by 100% compared with conventional Bose-Chaudhuri-Hocquenghem (BCH) error-correcting code (ECC). The second proposal, dynamic threshold voltage optimization (DVO) has two parts, adaptive V Ref shift (AVS) and V TH space control (VSC). AVS reduces read error and latency by adaptively optimizing the reference voltage (V Ref) based on temperature, W/E cycles and retention-time. AVS stores the optimal V Ref’s in a table in order to enable one cell read. VSC further improves AVS by optimizing the voltage margins between V TH states. DVO reduces BER by 80%.

Adaptive extended-state observer-based fault tolerant attitude control for spacecraft with reaction wheels

NASA Astrophysics Data System (ADS)

Ran, Dechao; Chen, Xiaoqian; de Ruiter, Anton; Xiao, Bing

2018-04-01

This study presents an adaptive second-order sliding control scheme to solve the attitude fault tolerant control problem of spacecraft subject to system uncertainties, external disturbances and reaction wheel faults. A novel fast terminal sliding mode is preliminarily designed to guarantee that finite-time convergence of the attitude errors can be achieved globally. Based on this novel sliding mode, an adaptive second-order observer is then designed to reconstruct the system uncertainties and the actuator faults. One feature of the proposed observer is that the design of the observer does not necessitate any priori information of the upper bounds of the system uncertainties and the actuator faults. In view of the reconstructed information supplied by the designed observer, a second-order sliding mode controller is developed to accomplish attitude maneuvers with great robustness and precise tracking accuracy. Theoretical stability analysis proves that the designed fault tolerant control scheme can achieve finite-time stability of the closed-loop system, even in the presence of reaction wheel faults and system uncertainties. Numerical simulations are also presented to demonstrate the effectiveness and superiority of the proposed control scheme over existing methodologies.

Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

NASA Astrophysics Data System (ADS)

Wang, L. M.

2017-09-01

A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master-slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

Adaptive hybrid optimal quantum control for imprecisely characterized systems.

PubMed

Egger, D J; Wilhelm, F K

2014-06-20

Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.

M-Adapting Low Order Mimetic Finite Differences for Dielectric Interface Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGregor, Duncan A.; Gyrya, Vitaliy; Manzini, Gianmarco

2016-03-07

We consider a problem of reducing numerical dispersion for electromagnetic wave in the domain with two materials separated by a at interface in 2D with a factor of two di erence in wave speed. The computational mesh in the homogeneous parts of the domain away from the interface consists of square elements. Here the method construction is based on m-adaptation construction in homogeneous domain that leads to fourth-order numerical dispersion (vs. second order in non-optimized method). The size of the elements in two domains also di ers by a factor of two, so as to preserve the same value ofmore » Courant number in each. Near the interface where two meshes merge the mesh with larger elements consists of degenerate pentagons. We demonstrate that prior to m-adaptation the accuracy of the method falls from second to rst due to breaking of symmetry in the mesh. Next we develop m-adaptation framework for the interface region and devise an optimization criteria. We prove that for the interface problem m-adaptation cannot produce increase in method accuracy. This is in contrast to homogeneous medium where m-adaptation can increase accuracy by two orders.« less

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Two degree of freedom internal model control-PID design for LFC of power systems via logarithmic approximations.

PubMed

Singh, Jay; Chattterjee, Kalyan; Vishwakarma, C B

2018-01-01

Load frequency controller has been designed for reduced order model of single area and two-area reheat hydro-thermal power system through internal model control - proportional integral derivative (IMC-PID) control techniques. The controller design method is based on two degree of freedom (2DOF) internal model control which combines with model order reduction technique. Here, in spite of taking full order system model a reduced order model has been considered for 2DOF-IMC-PID design and the designed controller is directly applied to full order system model. The Logarithmic based model order reduction technique is proposed to reduce the single and two-area high order power systems for the application of controller design.The proposed IMC-PID design of reduced order model achieves good dynamic response and robustness against load disturbance with the original high order system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Reduced error signalling in medication-naive children with ADHD: associations with behavioural variability and post-error adaptations

PubMed Central

Plessen, Kerstin J.; Allen, Elena A.; Eichele, Heike; van Wageningen, Heidi; Høvik, Marie Farstad; Sørensen, Lin; Worren, Marius Kalsås; Hugdahl, Kenneth; Eichele, Tom

2016-01-01

Background We examined the blood-oxygen level–dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). Methods We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8–12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. Results We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. Limitations Our study was limited by the modest sample size and imperfect matching across groups. Conclusion Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD. PMID:26441332

An experimental study of an adaptive-wall wind tunnel

NASA Technical Reports Server (NTRS)

Celik, Zeki; Roberts, Leonard

1988-01-01

A series of adaptive wall ventilated wind tunnel experiments was carried out to demonstrate the feasibility of using the side wall pressure distribution as the flow variable for the assessment of compatibility with free air conditions. Iterative and one step convergence methods were applied using the streamwise velocity component, the side wall pressure distribution and the normal velocity component in order to investigate their relative merits. The advantage of using the side wall pressure as the flow variable is to reduce the data taking time which is one the major contributors to the total testing time. In ventilated adaptive wall wind tunnel testing, side wall pressure measurements require simple instrumentation as opposed to the Laser Doppler Velocimetry used to measure the velocity components. In ventilated adaptive wall tunnel testing, influence coefficients are required to determine the pressure corrections in the plenum compartment. Experiments were carried out to evaluate the influence coefficients from side wall pressure distributions, and from streamwise and normal velocity distributions at two control levels. Velocity measurements were made using a two component Laser Doppler Velocimeter system.

3D numerical simulations of oblique droplet impact onto a deep liquid pool

NASA Astrophysics Data System (ADS)

Gelderblom, Hanneke; Reijers, Sten A.; Gielen, Marise; Sleutel, Pascal; Lohse, Detlef; Xie, Zhihua; Pain, Christopher C.; Matar, Omar K.

2017-11-01

We study the fluid dynamics of three-dimensional oblique droplet impact, which results in phenomena that include splashing and cavity formation. An adaptive, unstructured mesh modelling framework is employed here, which can modify and adapt unstructured meshes to better represent the underlying physics of droplet dynamics, and reduce computational effort without sacrificing accuracy. The numerical framework consists of a mixed control-volume and finite-element formulation, a volume-of-fluid-type method for the interface-capturing based on a compressive control-volume advection method. The framework also features second-order finite-element methods, and a force-balanced algorithm for the surface tension implementation, minimising the spurious velocities often found in many simulations involving capillary-driven flows. The numerical results generated using this framework are compared with high-speed images of the interfacial shapes of the deformed droplet, and the cavity formed upon impact, yielding good agreement. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

Algorithms for adaptive stochastic control for a class of linear systems

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R. V.

1977-01-01

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

Exploring Discretization Error in Simulation-Based Aerodynamic Databases

NASA Technical Reports Server (NTRS)

Aftosmis, Michael J.; Nemec, Marian

2010-01-01

This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.

New class of control laws for robotic manipulators. I - Nonadaptive case. II - Adaptive case

NASA Technical Reports Server (NTRS)

Wen, John T.; Bayard, David S.

1988-01-01

A new class of exponentially stabilizing control laws for joint level control of robot arms is discussed. Closed-loop exponential stability has been demonstrated for both the set point and tracking control problems by a slight modification of the energy Lyapunov function and the use of a lemma which handles third-order terms in the Lyapunov function derivatives. In the second part, these control laws are adapted in a simple fashion to achieve asymptotically stable adaptive control. The analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and uses a parameterization based on physical (time-invariant) quantities.

Adaptive wall wind tunnels: A selected, annotated bibliography

NASA Technical Reports Server (NTRS)

Tuttle, M. H.; Mineck, R. E.

1986-01-01

This bibliography, with abstracts, consists of 257 citations arranged in chronological order. Selection of the citations was made for their value to researchers working to solve problems associated with reducing wall interference by the design, development, and operation of adaptive wall test sections. Author, source, and subject indexes are included.

Effective learning strategies for real-time image-guided adaptive control of multiple-source hyperthermia applicators.

PubMed

Cheng, Kung-Shan; Dewhirst, Mark W; Stauffer, Paul R; Das, Shiva

2010-03-01

This paper investigates overall theoretical requirements for reducing the times required for the iterative learning of a real-time image-guided adaptive control routine for multiple-source heat applicators, as used in hyperthermia and thermal ablative therapy for cancer. Methods for partial reconstruction of the physical system with and without model reduction to find solutions within a clinically practical timeframe were analyzed. A mathematical analysis based on the Fredholm alternative theorem (FAT) was used to compactly analyze the existence and uniqueness of the optimal heating vector under two fundamental situations: (1) noiseless partial reconstruction and (2) noisy partial reconstruction. These results were coupled with a method for further acceleration of the solution using virtual source (VS) model reduction. The matrix approximation theorem (MAT) was used to choose the optimal vectors spanning the reduced-order subspace to reduce the time for system reconstruction and to determine the associated approximation error. Numerical simulations of the adaptive control of hyperthermia using VS were also performed to test the predictions derived from the theoretical analysis. A thigh sarcoma patient model surrounded by a ten-antenna phased-array applicator was retained for this purpose. The impacts of the convective cooling from blood flow and the presence of sudden increase of perfusion in muscle and tumor were also simulated. By FAT, partial system reconstruction directly conducted in the full space of the physical variables such as phases and magnitudes of the heat sources cannot guarantee reconstructing the optimal system to determine the global optimal setting of the heat sources. A remedy for this limitation is to conduct the partial reconstruction within a reduced-order subspace spanned by the first few maximum eigenvectors of the true system matrix. By MAT, this VS subspace is the optimal one when the goal is to maximize the average tumor temperature. When more than 6 sources present, the steps required for a nonlinear learning scheme is theoretically fewer than that of a linear one, however, finite number of iterative corrections is necessary for a single learning step of a nonlinear algorithm. Thus, the actual computational workload for a nonlinear algorithm is not necessarily less than that required by a linear algorithm. Based on the analysis presented herein, obtaining a unique global optimal heating vector for a multiple-source applicator within the constraints of real-time clinical hyperthermia treatments and thermal ablative therapies appears attainable using partial reconstruction with minimum norm least-squares method with supplemental equations. One way to supplement equations is the inclusion of a method of model reduction.

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

Composite adaptive control of belt polishing force for aero-engine blade

NASA Astrophysics Data System (ADS)

Zhsao, Pengbing; Shi, Yaoyao

2013-09-01

The existing methods for blade polishing mainly focus on robot polishing and manual grinding. Due to the difficulty in high-precision control of the polishing force, the blade surface precision is very low in robot polishing, in particular, quality of the inlet and exhaust edges can not satisfy the processing requirements. Manual grinding has low efficiency, high labor intensity and unstable processing quality, moreover, the polished surface is vulnerable to burn, and the surface precision and integrity are difficult to ensure. In order to further improve the profile accuracy and surface quality, a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed, which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together. By the mode decision-making mechanism, Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value, and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision. Based on the mathematical model of the force-exerting mechanism, simulation analysis is implemented on DSCAC. Simulation results show that the output polishing force can better track the given signal. Finally, the blade polishing experiments are carried out on the designed polishing equipment. Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility, valve dead-time effect, valve nonlinear flow, cylinder friction, measurement noise and other interference on the control precision of polishing force, which has high control precision, strong robustness, strong anti-interference ability and other advantages compared with MRACFNN. The proposed research achieves high-precision control of the polishing force, effectively improves the blade machining precision and surface consistency, and significantly reduces the surface roughness.

Simple adaptive control system design for a quadrotor with an internal PFC

NASA Astrophysics Data System (ADS)

Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto; Takagi, Taro

2014-12-01

The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loop of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations.

Flight Test Comparison of Different Adaptive Augmentations for Fault Tolerant Control Laws for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Hanson, Curtis E.; Lee, James A.; Kaneshige, John T.

2009-01-01

This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.

[Application of adaptive canceling methods in temperature control in ultrasonic therapeutical treatment].

PubMed

Deng, Jun; Liu, Du-ren

2002-12-01

Objective. To improve the quality of ultrasonic therapeutical treatment by improving the accuracy of temperature control. Method. Adaptive canceling methods were used to reduce the noise of temperature signal gained, and enhance signal-to-noise ratio. Result. The test's result corresponds basically to the theoretical curve. Conclusion. Adaptive canceling methods can be applied to clinic treatment.

Adaptive Engine Technologies for Aviation CO2 Emissions Reduction

NASA Technical Reports Server (NTRS)

Mercer, Carolyn R.; Haller, William J.; Tong, Michael T.

2006-01-01

Adaptive turbine engine technologies are assessed for their potential to reduce carbon dioxide emissions from commercial air transports.Technologies including inlet, fan, and compressor flow control, compressor stall control, blade clearance control, combustion control, active bearings and enabling technologies such as active materials and wireless sensors are discussed. The method of systems assessment is described, including strengths and weaknesses of the approach. Performance benefit estimates are presented for each technology, with a summary of potential emissions reduction possible from the development of new, adaptively controlled engine components.

75 FR 34726 - Energy Conservation Program for Consumer Products: Notice of Petition for Waiver of LG...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-18

... relative humidity sensors and adaptive control anti-sweat heaters. The rationale for granting these waivers is equally applicable to LG, which has products containing similar relative humidity sensors and anti... humidity sensors and adaptive control anti-sweat heaters. Therefore, it is ordered that: The application...

Adaptive feedforward control of non-minimum phase structural systems

NASA Astrophysics Data System (ADS)

Vipperman, J. S.; Burdisso, R. A.

1995-06-01

Adaptive feedforward control algorithms have been effectively applied to stationary disturbance rejection. For structural systems, the ideal feedforward compensator is a recursive filter which is a function of the transfer functions between the disturbance and control inputs and the error sensor output. Unfortunately, most control configurations result in a non-minimum phase control path; even a collocated control actuator and error sensor will not necessarily produce a minimum phase control path in the discrete domain. Therefore, the common practice is to choose a suitable approximation of the ideal compensator. In particular, all-zero finite impulse response (FIR) filters are desirable because of their inherent stability for adaptive control approaches. However, for highly resonant systems, large order filters are required for broadband applications. In this work, a control configuration is investigated for controlling non-minimum phase lightly damped structural systems. The control approach uses low order FIR filters as feedforward compensators in a configuration that has one more control actuator than error sensors. The performance of the controller was experimentally evaluated on a simply supported plate under white noise excitation for a two-input, one-output (2I1O) system. The results show excellent error signal reduction, attesting to the effectiveness of the method.

Understanding adaptive gait in lower-limb amputees: insights from multivariate analyses

PubMed Central

2013-01-01

Background In this paper we use multivariate statistical techniques to gain insights into how adaptive gait involving obstacle crossing is regulated in lower-limb amputees compared to able-bodied controls, with the aim of identifying underlying characteristics that differ between the two groups and consequently highlighting gait deficits in the amputees. Methods Eight unilateral trans-tibial amputees and twelve able-bodied controls completed adaptive gait trials involving negotiating various height obstacles; with amputees leading with their prosthetic limb. Spatiotemporal variables that are regularly used to quantify how gait is adapted when crossing obstacles were determined and subsequently analysed using multivariate statistical techniques. Results and discussion There were fundamental differences in the adaptive gait between the two groups. Compared to controls, amputees had a reduced approach velocity, reduced foot placement distance before and after the obstacle and reduced foot clearance over it, and reduced lead-limb knee flexion during the step following crossing. Logistic regression analysis highlighted the variables that best distinguished between the gait of the two groups and multiple regression analysis (with approach velocity as a controlling factor) helped identify what gait adaptations were driving the differences seen in these variables. Getting closer to the obstacle before crossing it appeared to be a strategy to ensure the heel of the lead-limb foot passed over the obstacle prior to the foot being lowered to the ground. Despite adopting such a heel clearance strategy, the lead-foot was positioned closer to the obstacle following crossing, which was likely a result of a desire to attain a limb/foot angle and orientation at instant of landing that minimised loads on the residuum (as evidenced by the reduced lead-limb knee flexion during the step following crossing). These changes in foot placement meant the foot was in a different part of swing at point of crossing and this explains why foot clearance was considerably reduced in amputees. Conclusions These results highlight that trans-tibial amputees use quite different gait adaptations to cross obstacles compared with controls (at least when leading with their prosthetic limb), indicating they are governed by different constraints; seemingly related to how they land on/load their prosthesis after crossing the obstacle. PMID:23958032

The role of stimulus-specific adaptation in songbird syntax generation

NASA Astrophysics Data System (ADS)

Wittenbach, Jason D.

Sequential behaviors are an important part of the behavioral repertoire of many animals and understanding how neural circuits encode and generate such sequences is a long-standing question in neuroscience. The Bengalese finch is a useful model system for studying variable action sequences. The songs of these birds consist of well-defined vocal elements (syllables) that are strung together to form sequences. The ordering of the syllables within the sequence is variable but not random - it shows complex statistical patterns (syntax). While often thought to be first-order, the syntax of the Bengalese finch song shows a distinct form of history dependence where the probability of repeating a syllable decreases as a function of the number of repetitions that have already occurred. Current models of the Bengalese finch song control circuitry offer no explanation for this repetition adaptation. The Bengalese finch also uses real-time auditory feedback to control the song syntax. Considering these facts, we hypothesize that repetition adaptation in the Bengalese finch syntax may be caused by stimulus-specific adaptation - a wide-spread phenomenon where neural responses to a specific stimulus become weaker with repeated presentations of the same stimulus. We begin by proposing a computational model for the song-control circuit where an auditory feedback signal that undergoes stimulus-specific adaptation helps drive repeated syllables. We show that this model does indeed capture the repetition adaptation observed in Bengalese finch syntax; along the way, we derive a new probabilistic model for repetition adaptation. Key predictions of our model are analyzed in light of experiments performed by collaborators. Next we extend the model in order to predict how the syntax will change as a function of brain temperature. These predictions are compared to experimental results from collaborators where portions of the Bengalese finch song circuit are cooled in awake and behaving birds. Finally we show that repetition adaptation persists even in a simplified dynamical system model when a parameter controlling the repeat probability changes slowly over repetitions.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Model Reduction for Control System Design

NASA Technical Reports Server (NTRS)

Enns, D. F.

1985-01-01

An approach and a technique for effectively obtaining reduced order mathematical models of a given large order model for the purposes of synthesis, analysis and implementation of control systems is developed. This approach involves the use of an error criterion which is the H-infinity norm of a frequency weighted error between the full and reduced order models. The weightings are chosen to take into account the purpose for which the reduced order model is intended. A previously unknown error bound in the H-infinity norm for reduced order models obtained from internally balanced realizations was obtained. This motivated further development of the balancing technique to include the frequency dependent weightings. This resulted in the frequency weighted balanced realization and a new model reduction technique. Two approaches to designing reduced order controllers were developed. The first involves reducing the order of a high order controller with an appropriate weighting. The second involves linear quadratic Gaussian synthesis based on a reduced order model obtained with an appropriate weighting.

Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

NASA Astrophysics Data System (ADS)

Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

2017-09-01

In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

A locally p-adaptive approach for Large Eddy Simulation of compressible flows in a DG framework

NASA Astrophysics Data System (ADS)

Tugnoli, Matteo; Abbà, Antonella; Bonaventura, Luca; Restelli, Marco

2017-11-01

We investigate the possibility of reducing the computational burden of LES models by employing local polynomial degree adaptivity in the framework of a high-order DG method. A novel degree adaptation technique especially featured to be effective for LES applications is proposed and its effectiveness is compared to that of other criteria already employed in the literature. The resulting locally adaptive approach allows to achieve significant reductions in computational cost of representative LES computations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doss, Mohan

Oxidative damage has been implicated in the pathogenesis of most aging-related diseases including neurodegenerative diseases. Antioxidant supplementation has been found to be ineffective in reducing such diseases, but increased endogenous production of antioxidants from the adaptive response due to physical and cognitive exercises (which increase oxidative metabolism and oxidative stress) has been effective in reducing some of the diseases. Low dose radiation (LDR), which increases oxidative stress and results in adaptive response of increased antioxidants, may provide an alternative method of controlling the aging-related diseases. We have studied the effect of LDR on the induction of adaptive response in ratmore » brains and the effectiveness of the LDR in reducing the oxidative damage caused by subsequent high dose radiation. We have also investigated the effect of LDR on apomorphine-induced rotations in the 6-hydroxydopamine (6-OHDA) unilaterally-lesioned rat model of Parkinson?s disease (PD). LDR was observed to initiate an adaptive response in the brain, and reduce the oxidative damage from subsequent high dose radiation exposure, confirming the effectiveness of LDR adaptive response in reducing the oxidative damage from the free radicals due to high dose radiation. LDR resulted in a slight improvement in Tyrosine hydroxylase expression on the lesioned side of substantia nigra (indicative of its protective effect on the dopaminergic neurons), and reduced the behavioral symptoms in the 6-OHDA rat model of PD. Translation of this concept to humans, if found to be applicable, may be a possible approach for controlling the progression of PD and other neurodegenerative diseases. Since any translation of the concept to humans would be hindered by the currently prevalent carcinogenic concerns regarding LDR based on the linear no-threshold (LNT) model, we have also studied the justifications for the use of the LNT model. One of the shortcomings of the LNT model is that it ignores the effects of any adaptive response of the body to the LDR. The importance of considering adaptive response becomes obvious when one considers the sharp contrast between (i) the failure of well-designed anti-angiogenesis therapies which resulted in aggressive tumors because of ignoring adaptive response and (ii) the occasional cure of untreated metastatic lesions likely due to the incidental adaptive response from the LDR exposure to parts of the body during radiation therapy of a primary tumor, known as the abscopal effect. Another shortcoming of the LNT model is that it pays exclusive attention to increase in mutations, which is not a decisive factor in the occurrence of clinical cancers, as the cause of excess cancers. On the other hand, LNT model ignores the immune system response, which plays a very important role in preventing occult cancers from becoming clinical cancers, as demonstrated by the large increase in cancers in organ transplant patients whose immune system is suppressed. There is also recent epidemiological evidence against the LNT model. A re-analysis of the latest update to the atomic bomb survivor data has shown that the data no longer support the LNT model but are consistent with the radiation hormesis hypothesis. A re-analysis of cancer incidence data of Taiwanese apartment dwellers that were exposed to LDR from contaminated building materials has also shown a reduction in cancers from the LDR. The present LDR carcinogenic concerns would preclude any human study of cancer prevention using LDR, since the study would require subjecting a large asymptomatic population to LDR. However, pilot studies of radiation hormesis in cancer patients may be more acceptable since these would require irradiation of limited numbers of patients in order to assess the effectiveness of the LDR treatments. Some of the LDR applications that may be considered for cancer patients are: LDR treatment of early stage cancers without the adverse side effects of current treatments such as radiation therapy or chemotherapy, adjuvant LDR treatment of cancer patients undergoing radiation therapy for better tumor control and reduced metastasis, and the use of LDR treatment following radiation therapy to reduce the risk of second cancers from the radiation therapy. Studies of LDR for the control of early-stage neurodegenerative diseases may also be more acceptable since currently there are no effective treatments available for controlling these diseases, and since such studies would require LDR exposure to limited parts of the brain, and the carcinogenic risk from such treatments would be very small due to the low radiation tissue-weighting factor for the brain. Success in these studies can lead to the study of LDR for preventing and controlling other aging-related diseases.« less

Two biomechanical strategies for locomotor adaptation to split-belt treadmill walking in subjects with and without transtibial amputation.

PubMed

Selgrade, Brian P; Toney, Megan E; Chang, Young-Hui

2017-02-28

Locomotor adaptation is commonly studied using split-belt treadmill walking, in which each foot is placed on a belt moving at a different speed. As subjects adapt to split-belt walking, they reduce metabolic power, but the biomechanical mechanism behind this improved efficiency is unknown. Analyzing mechanical work performed by the legs and joints during split-belt adaptation could reveal this mechanism. Because ankle work in the step-to-step transition is more efficient than hip work, we hypothesized that control subjects would reduce hip work on the fast belt and increase ankle work during the step-to-step transition as they adapted. We further hypothesized that subjects with unilateral, trans-tibial amputation would instead increase propulsive work from their intact leg on the slow belt. Control subjects reduced hip work and shifted more ankle work to the step-to-step transition, supporting our hypothesis. Contrary to our second hypothesis, intact leg work, ankle work and hip work in amputees were unchanged during adaptation. Furthermore, all subjects increased collisional energy loss on the fast belt, but did not increase propulsive work. This was possible because subjects moved further backward during fast leg single support in late adaptation than in early adaptation, compensating by reducing backward movement in slow leg single support. In summary, subjects used two strategies to improve mechanical efficiency in split-belt walking adaptation: a CoM displacement strategy that allows for less forward propulsion on the fast belt; and, an ankle timing strategy that allows efficient ankle work in the step-to-step transition to increase while reducing inefficient hip work. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays.

PubMed

Tong, Shao Cheng; Li, Yong Ming; Zhang, Hua-Guang

2011-07-01

In this paper, two adaptive neural network (NN) decentralized output feedback control approaches are proposed for a class of uncertain nonlinear large-scale systems with immeasurable states and unknown time delays. Using NNs to approximate the unknown nonlinear functions, an NN state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping technique with decentralized control design principle, an adaptive NN decentralized output feedback control approach is developed. In order to overcome the problem of "explosion of complexity" inherent in the proposed control approach, the dynamic surface control (DSC) technique is introduced into the first adaptive NN decentralized control scheme, and a simplified adaptive NN decentralized output feedback DSC approach is developed. It is proved that the two proposed control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the observer errors and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approaches.

Sensory Adapted Dental Environments to Enhance Oral Care for Children with Autism Spectrum Disorders: A Randomized Controlled Pilot Study

PubMed Central

Cermak, Sharon A.; Stein Duker, Leah I.; Williams, Marian E.; Dawson, Michael E.; Lane, Christianne J.; Polido, José C.

2015-01-01

This pilot and feasibility study examined the impact of a sensory adapted dental environment (SADE) to reduce distress, sensory discomfort, and perception of pain during oral prophylaxis for children with autism spectrum disorder (ASD). Participants were 44 children ages 6-12 (n=22 typical, n=22 ASD). In an experimental crossover design, each participant underwent two professional dental cleanings, one in a regular dental environment (RDE) and one in a SADE, administered in a randomized and counterbalanced order three to four months apart. Outcomes included measures of physiological anxiety, behavioral distress, pain intensity, and sensory discomfort. Both groups exhibited decreased physiological anxiety and reported lower pain and sensory discomfort in the SADE condition compared to RDE, indicating a beneficial effect of the SADE. PMID:25931290

An investigation of adaptive controllers for helicopter vibration and the development of a new dual controller

NASA Technical Reports Server (NTRS)

Mookerjee, P.; Molusis, J. A.; Bar-Shalom, Y.

1985-01-01

An investigation of the properties important for the design of stochastic adaptive controllers for the higher harmonic control of helicopter vibration is presented. Three different model types are considered for the transfer relationship between the helicopter higher harmonic control input and the vibration output: (1) nonlinear; (2) linear with slow time varying coefficients; and (3) linear with constant coefficients. The stochastic controller formulations and solutions are presented for a dual, cautious, and deterministic controller for both linear and nonlinear transfer models. Extensive simulations are performed with the various models and controllers. It is shown that the cautious adaptive controller can sometimes result in unacceptable vibration control. A new second order dual controller is developed which is shown to modify the cautious adaptive controller by adding numerator and denominator correction terms to the cautious control algorithm. The new dual controller is simulated on a simple single-control vibration example and is found to achieve excellent vibration reduction and significantly improves upon the cautious controller.

Disturbance observer-based adaptive sliding mode hybrid projective synchronisation of identical fractional-order financial systems

NASA Astrophysics Data System (ADS)

Khan, Ayub; Tyagi, Arti

2018-05-01

In this paper, we have studied the hybrid projective synchronisation for incommensurate, integer and commensurate fractional-order financial systems with unknown disturbance. To tackle the problem of unknown bounded disturbance, fractional-order disturbance observer is designed to approximate the unknown disturbance. Further, we have introduced simple sliding mode surface and designed adaptive sliding mode controllers incorporating with the designed fractional-order disturbance observer to achieve a bounded hybrid projective synchronisation between two identical fractional-order financial model with different initial conditions. It is shown that the slave system with disturbance can be synchronised with the projection of the master system generated through state transformation. Simulation results are presented to ensure the validity and effectiveness of the proposed sliding mode control scheme in the presence of external bounded unknown disturbance. Also, synchronisation error for commensurate, integer and incommensurate fractional-order financial systems is studied in numerical simulation.

Simple adaptive control system design for a quadrotor with an internal PFC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto

2014-12-10

The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loopmore » of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations.« less

High-resolution wavefront control of high-power laser systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brase, J; Brown, C; Carrano, C

1999-07-08

Nearly every new large-scale laser system application at LLNL has requirements for beam control which exceed the current level of available technology. For applications such as inertial confinement fusion, laser isotope separation, laser machining, and laser the ability to transport significant power to a target while maintaining good beam quality is critical. There are many ways that laser wavefront quality can be degraded. Thermal effects due to the interaction of high-power laser or pump light with the internal optical components or with the ambient gas are common causes of wavefront degradation. For many years, adaptive optics based on thing deformablemore » glass mirrors with piezoelectric or electrostrictive actuators have be used to remove the low-order wavefront errors from high-power laser systems. These adaptive optics systems have successfully improved laser beam quality, but have also generally revealed additional high-spatial-frequency errors, both because the low-order errors have been reduced and because deformable mirrors have often introduced some high-spatial-frequency components due to manufacturing errors. Many current and emerging laser applications fall into the high-resolution category where there is an increased need for the correction of high spatial frequency aberrations which requires correctors with thousands of degrees of freedom. The largest Deformable Mirrors currently available have less than one thousand degrees of freedom at a cost of approximately $1M. A deformable mirror capable of meeting these high spatial resolution requirements would be cost prohibitive. Therefore a new approach using a different wavefront control technology is needed. One new wavefront control approach is the use of liquid-crystal (LC) spatial light modulator (SLM) technology for the controlling the phase of linearly polarized light. Current LC SLM technology provides high-spatial-resolution wavefront control, with hundreds of thousands of degrees of freedom, more than two orders of magnitude greater than the best Deformable Mirrors currently made. Even with the increased spatial resolution, the cost of these devices is nearly two orders of magnitude less than the cost of the largest deformable mirror.« less

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

PubMed Central

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-12-19

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

PubMed

Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

2017-03-01

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

Event-Triggered Adaptive Dynamic Programming for Continuous-Time Systems With Control Constraints.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2016-08-31

In this paper, an event-triggered near optimal control structure is developed for nonlinear continuous-time systems with control constraints. Due to the saturating actuators, a nonquadratic cost function is introduced and the Hamilton-Jacobi-Bellman (HJB) equation for constrained nonlinear continuous-time systems is formulated. In order to solve the HJB equation, an actor-critic framework is presented. The critic network is used to approximate the cost function and the action network is used to estimate the optimal control law. In addition, in the proposed method, the control signal is transmitted in an aperiodic manner to reduce the computational and the transmission cost. Both the networks are only updated at the trigger instants decided by the event-triggered condition. Detailed Lyapunov analysis is provided to guarantee that the closed-loop event-triggered system is ultimately bounded. Three case studies are used to demonstrate the effectiveness of the proposed method.

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Incident management under SCAT adaptive control system : FAST-TRAC phase III deliverable. #11, Final report on incident management under SCATS adaptive control system

DOT National Transportation Integrated Search

1998-04-01

The report documents the results of a study designed to test the effectiveness of ATMS and ATIS strategies to reduce delay resulting from an incident. The study had two main sections: a simulation study to test the effectiveness of several control st...

Plant Hormesis Management with Biostimulants of Biotic Origin in Agriculture.

PubMed

Vargas-Hernandez, Marcela; Macias-Bobadilla, Israel; Guevara-Gonzalez, Ramon G; Romero-Gomez, Sergio de J; Rico-Garcia, Enrique; Ocampo-Velazquez, Rosalia V; Alvarez-Arquieta, Luz de L; Torres-Pacheco, Irineo

2017-01-01

Over time plants developed complex mechanisms in order to adapt themselves to the environment. Plant innate immunity is one of the most important mechanisms for the environmental adaptation. A myriad of secondary metabolites with nutraceutical features are produced by the plant immune system in order to get adaptation to new environments that provoke stress (stressors). Hormesis is a phenomenon by which a stressor (i.e., toxins, herbicides, etc.) stimulates the cellular stress response, including secondary metabolites production, in order to help organisms to establish adaptive responses. Hormetins of biotic origin (i.e., biostimulants or biological control compounds), in certain doses might enhance plant performance, however, in excessive doses they are commonly deleterious. Biostimulants or biological control compounds of biotic origin are called "elicitors" that have widely been studied as inducers of plant tolerance to biotic and abiotic stresses. The plant response toward elicitors is reminiscent of hormetic responses toward toxins in several organisms. Thus, controlled management of hormetic responses in plants using these types of compounds is expected to be an important tool to increase nutraceutical quality of plant food and trying to minimize negative effects on yields. The aim of this review is to analyze the potential for agriculture that the use of biostimulants and biological control compounds of biotic origin could have in the management of the plant hormesis. The use of homolog DNA as biostimulant or biological control compound in crop production is also discussed.

Plant Hormesis Management with Biostimulants of Biotic Origin in Agriculture

PubMed Central

Vargas-Hernandez, Marcela; Macias-Bobadilla, Israel; Guevara-Gonzalez, Ramon G.; Romero-Gomez, Sergio de J.; Rico-Garcia, Enrique; Ocampo-Velazquez, Rosalia V.; Alvarez-Arquieta, Luz de L.; Torres-Pacheco, Irineo

2017-01-01

Over time plants developed complex mechanisms in order to adapt themselves to the environment. Plant innate immunity is one of the most important mechanisms for the environmental adaptation. A myriad of secondary metabolites with nutraceutical features are produced by the plant immune system in order to get adaptation to new environments that provoke stress (stressors). Hormesis is a phenomenon by which a stressor (i.e., toxins, herbicides, etc.) stimulates the cellular stress response, including secondary metabolites production, in order to help organisms to establish adaptive responses. Hormetins of biotic origin (i.e., biostimulants or biological control compounds), in certain doses might enhance plant performance, however, in excessive doses they are commonly deleterious. Biostimulants or biological control compounds of biotic origin are called “elicitors” that have widely been studied as inducers of plant tolerance to biotic and abiotic stresses. The plant response toward elicitors is reminiscent of hormetic responses toward toxins in several organisms. Thus, controlled management of hormetic responses in plants using these types of compounds is expected to be an important tool to increase nutraceutical quality of plant food and trying to minimize negative effects on yields. The aim of this review is to analyze the potential for agriculture that the use of biostimulants and biological control compounds of biotic origin could have in the management of the plant hormesis. The use of homolog DNA as biostimulant or biological control compound in crop production is also discussed. PMID:29081787

Adaptive control and noise suppression by a variable-gain gradient algorithm

NASA Technical Reports Server (NTRS)

Merhav, S. J.; Mehta, R. S.

1987-01-01

An adaptive control system based on normalized LMS filters is investigated. The finite impulse response of the nonparametric controller is adaptively estimated using a given reference model. Specifically, the following issues are addressed: The stability of the closed loop system is analyzed and heuristically established. Next, the adaptation process is studied for piecewise constant plant parameters. It is shown that by introducing a variable-gain in the gradient algorithm, a substantial reduction in the LMS adaptation rate can be achieved. Finally, process noise at the plant output generally causes a biased estimate of the controller. By introducing a noise suppression scheme, this bias can be substantially reduced and the response of the adapted system becomes very close to that of the reference model. Extensive computer simulations validate these and demonstrate assertions that the system can rapidly adapt to random jumps in plant parameters.

Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arrighi, Bill

2016-03-03

libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.

Sleep deprivation reduces perceived emotional intelligence and constructive thinking skills.

PubMed

Killgore, William D S; Kahn-Greene, Ellen T; Lipizzi, Erica L; Newman, Rachel A; Kamimori, Gary H; Balkin, Thomas J

2008-07-01

Insufficient sleep can adversely affect a variety of cognitive abilities, ranging from simple alertness to higher-order executive functions. Although the effects of sleep loss on mood and cognition are well documented, there have been no controlled studies examining its effects on perceived emotional intelligence (EQ) and constructive thinking, abilities that require the integration of affect and cognition and are central to adaptive functioning. Twenty-six healthy volunteers completed the Bar-On Emotional Quotient Inventory (EQi) and the Constructive Thinking Inventory (CTI) at rested baseline and again after 55.5 and 58 h of continuous wakefulness, respectively. Relative to baseline, sleep deprivation was associated with lower scores on Total EQ (decreased global emotional intelligence), Intrapersonal functioning (reduced self-regard, assertiveness, sense of independence, and self-actualization), Interpersonal functioning (reduced empathy toward others and quality of interpersonal relationships), Stress Management skills (reduced impulse control and difficulty with delay of gratification), and Behavioral Coping (reduced positive thinking and action orientation). Esoteric Thinking (greater reliance on formal superstitions and magical thinking processes) was increased. These findings are consistent with the neurobehavioral model suggesting that sleep loss produces temporary changes in cerebral metabolism, cognition, emotion, and behavior consistent with mild prefrontal lobe dysfunction.

Performance Evaluation of Multichannel Adaptive Algorithms for Local Active Noise Control

NASA Astrophysics Data System (ADS)

DE DIEGO, M.; GONZALEZ, A.

2001-07-01

This paper deals with the development of a multichannel active noise control (ANC) system inside an enclosed space. The purpose is to design a real practical system which works well in local ANC applications. Moreover, the algorithm implemented in the adaptive controller should be robust, of low computational complexity and it should manage to generate a uniform useful-size zone of quite in order to allow the head motion of a person seated on a seat inside a car. Experiments were carried out under semi-anechoic and listening room conditions to verify the successful implementation of the multichannel system. The developed prototype consists of an array of up to four microphones used as error sensors mounted on the headrest of a seat place inside the enclosure. One loudspeaker was used as single primary source and two secondary sources were placed facing the seat. The aim of this multichannel system is to reduce the sound pressure levels in an area around the error sensors, following a local control strategy. When using this technique, the cancellation points are not only the error sensor positions but an area around them, which is measured by using a monitoring microphone. Different multichannel adaptive algorithms for ANC have been analyzed and their performance verified. Multiple error algorithms are used in order to cancel out different types of primary noise (engine noise and random noise) with several configurations (up to four channels system). As an alternative to the multiple error LMS algorithm (multichannel version of the filtered-X LMS algorithm, MELMS), the least maximum mean squares (LMMS) and the scanning error-LMS algorithm have been developed in this work in order to reduce computational complexity and achieve a more uniform residual field. The ANC algorithms were programmed on a digital signal processing board equipped with a TMS320C40 floating point DSP processor. Measurements concerning real-time experiments on local noise reduction in two environments and at frequencies below 230 Hz are presented. Better noise levels attenuation is obtained in the semianechoic chamber due to the simplicity of the acoustic field. The size of the zone of quiet makes the system useful at relatively low frequencies and it is large enough to cover a listener's head movements. The spatial extent of the zones of quiet is generally observed to increase as the error sensors are moved away from the secondary source, they are put closer together or its number increases. In summary, different algorithms' performance and the viability of the multichannel system for local active noise control in real listening conditions are evaluated and some guidelines for designing such systems are then proposed.

A new instantaneous torque control of PM synchronous motor for high-performance direct-drive applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, S.K.; Kim, H.S.; Kim, C.G.

1998-05-01

a new instantaneous torque-control strategy is presented for high-performance control of a permanent magnet (PM) synchronous motor. In order to deal with the torque pulsating problem of a PM synchronous motor in a low-speed region, new torque estimation and control techniques are proposed. The linkage flux of a PM synchronous motor is estimated using a model reference adaptive system technique, and the developed torque is instantaneously controlled by the proposed torque controller combining a variable structure control (VSC) with a space-vector pulse-width modulation (PWM). The proposed control provides the advantage of reducing the torque pulsation caused by the nonsinusoidal fluxmore » distribution. This control strategy is applied to the high-torque PM synchronous motor drive system for direct-drive applications and implemented by using a software of the digital signal processor (DSP) TMS320C30. The simulations and experiments are carried out for this system, and the results well demonstrate the effectiveness of the proposed control.« less

Triggering the adaptive immune system with commensal gut bacteria protects against insulin resistance and dysglycemia.

PubMed

Pomié, Céline; Blasco-Baque, Vincent; Klopp, Pascale; Nicolas, Simon; Waget, Aurélie; Loubières, Pascale; Azalbert, Vincent; Puel, Anthony; Lopez, Frédéric; Dray, Cédric; Valet, Philippe; Lelouvier, Benjamin; Servant, Florence; Courtney, Michael; Amar, Jacques; Burcelin, Rémy; Garidou, Lucile

2016-06-01

To demonstrate that glycemia and insulin resistance are controlled by a mechanism involving the adaptive immune system and gut microbiota crosstalk. We triggered the immune system with microbial extracts specifically from the intestinal ileum contents of HFD-diabetic mice by the process of immunization. 35 days later, immunized mice were fed a HFD for up to two months in order to challenge the development of metabolic features. The immune responses were quantified. Eventually, adoptive transfer of immune cells from the microbiota-immunized mice to naïve mice was performed to demonstrate the causality of the microbiota-stimulated adaptive immune system on the development of metabolic disease. The gut microbiota of the immunized HFD-fed mice was characterized in order to demonstrate whether the manipulation of the microbiota to immune system interaction reverses the causal deleterious effect of gut microbiota dysbiosis on metabolic disease. Subcutaneous injection (immunization procedure) of ileum microbial extracts prevented hyperglycemia and insulin resistance in a dose-dependent manner in response to a HFD. The immunization enhanced the proliferation of CD4 and CD8 T cells in lymphoid organs, also increased cytokine production and antibody secretion. As a mechanism explaining the metabolic improvement, the immunization procedure reversed gut microbiota dysbiosis. Finally, adoptive transfer of immune cells from immunized mice improved metabolic features in response to HFD. Glycemia and insulin sensitivity can be regulated by triggering the adaptive immunity to microbiota interaction. This reduces the gut microbiota dysbiosis induced by a fat-enriched diet.

Study on Fuzzy Adaptive Fractional Order PIλDμ Control for Maglev Guiding System

NASA Astrophysics Data System (ADS)

Hu, Qing; Hu, Yuwei

The mathematical model of the linear elevator maglev guiding system is analyzed in this paper. For the linear elevator needs strong stability and robustness to run, the integer order PID was expanded to the fractional order, in order to improve the steady state precision, rapidity and robustness of the system, enhance the accuracy of the parameter in fractional order PIλDμ controller, the fuzzy control is combined with the fractional order PIλDμ control, using the fuzzy logic achieves the parameters online adjustment. The simulations reveal that the system has faster response speed, higher tracking precision, and has stronger robustness to the disturbance.

Projection Operator: A Step Towards Certification of Adaptive Controllers

NASA Technical Reports Server (NTRS)

Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control

PubMed Central

Nachstedt, Timo; Tetzlaff, Christian; Manoonpong, Poramate

2017-01-01

Rhythmic neural signals serve as basis of many brain processes, in particular of locomotion control and generation of rhythmic movements. It has been found that specific neural circuits, named central pattern generators (CPGs), are able to autonomously produce such rhythmic activities. In order to tune, shape and coordinate the produced rhythmic activity, CPGs require sensory feedback, i.e., external signals. Nonlinear oscillators are a standard model of CPGs and are used in various robotic applications. A special class of nonlinear oscillators are adaptive frequency oscillators (AFOs). AFOs are able to adapt their frequency toward the frequency of an external periodic signal and to keep this learned frequency once the external signal vanishes. AFOs have been successfully used, for instance, for resonant tuning of robotic locomotion control. However, the choice of parameters for a standard AFO is characterized by a trade-off between the speed of the adaptation and its precision and, additionally, is strongly dependent on the range of frequencies the AFO is confronted with. As a result, AFOs are typically tuned such that they require a comparably long time for their adaptation. To overcome the problem, here, we improve the standard AFO by introducing a novel adaptation mechanism based on dynamical coupling strengths. The dynamical adaptation mechanism enhances both the speed and precision of the frequency adaptation. In contrast to standard AFOs, in this system, the interplay of dynamics on short and long time scales enables fast as well as precise adaptation of the oscillator for a wide range of frequencies. Amongst others, a very natural implementation of this mechanism is in terms of neural networks. The proposed system enables robotic applications which require fast retuning of locomotion control in order to react to environmental changes or conditions. PMID:28377710

Novel modes and adaptive block scanning order for intra prediction in AV1

NASA Astrophysics Data System (ADS)

Hadar, Ofer; Shleifer, Ariel; Mukherjee, Debargha; Joshi, Urvang; Mazar, Itai; Yuzvinsky, Michael; Tavor, Nitzan; Itzhak, Nati; Birman, Raz

2017-09-01

The demand for streaming video content is on the rise and growing exponentially. Networks bandwidth is very costly and therefore there is a constant effort to improve video compression rates and enable the sending of reduced data volumes while retaining quality of experience (QoE). One basic feature that utilizes the spatial correlation of pixels for video compression is Intra-Prediction, which determines the codec's compression efficiency. Intra prediction enables significant reduction of the Intra-Frame (I frame) size and, therefore, contributes to efficient exploitation of bandwidth. In this presentation, we propose new Intra-Prediction algorithms that improve the AV1 prediction model and provide better compression ratios. Two (2) types of methods are considered: )1( New scanning order method that maximizes spatial correlation in order to reduce prediction error; and )2( New Intra-Prediction modes implementation in AVI. Modern video coding standards, including AVI codec, utilize fixed scan orders in processing blocks during intra coding. The fixed scan orders typically result in residual blocks with high prediction error mainly in blocks with edges. This means that the fixed scan orders cannot fully exploit the content-adaptive spatial correlations between adjacent blocks, thus the bitrate after compression tends to be large. To reduce the bitrate induced by inaccurate intra prediction, the proposed approach adaptively chooses the scanning order of blocks according to criteria of firstly predicting blocks with maximum number of surrounding, already Inter-Predicted blocks. Using the modified scanning order method and the new modes has reduced the MSE by up to five (5) times when compared to conventional TM mode / Raster scan and up to two (2) times when compared to conventional CALIC mode / Raster scan, depending on the image characteristics (which determines the percentage of blocks predicted with Inter-Prediction, which in turn impacts the efficiency of the new scanning method). For the same cases, the PSNR was shown to improve by up to 7.4dB and up to 4 dB, respectively. The new modes have yielded 5% improvement in BD-Rate over traditionally used modes, when run on K-Frame, which is expected to yield 1% of overall improvement.

Adaptive Nulling for the Terrestrial Planet Finder Interferometer

NASA Technical Reports Server (NTRS)

Peters, Robert D.; Lay, Oliver P.; Jeganathan, Muthu; Hirai, Akiko

2006-01-01

A description of adaptive nulling for Terrestrial Planet Finder Interferometer (TPFI) is presented. The topics include: 1) Nulling in TPF-I; 2) Why Do Adaptive Nulling; 3) Parallel High-Order Compensator Design; 4) Phase and Amplitude Control; 5) Development Activates; 6) Requirements; 7) Simplified Experimental Setup; 8) Intensity Correction; and 9) Intensity Dispersion Stability. A short summary is also given on adaptive nulling for the TPFI.

Adaptive method for electron bunch profile prediction

DOE PAGES

Scheinker, Alexander; Gessner, Spencer

2015-10-15

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. Thus, the simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrialmore » control system. Finally, the main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.« less

Design of sewage treatment system by applying fuzzy adaptive PID controller

NASA Astrophysics Data System (ADS)

Jin, Liang-Ping; Li, Hong-Chan

2013-03-01

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

Evaluation of early antimicrobial therapy adaptation guided by the BetaLACTA® test: a case-control study.

PubMed

Garnier, Marc; Rozencwajg, Sacha; Pham, Tài; Vimont, Sophie; Blayau, Clarisse; Hafiani, Mehdi; Fulgencio, Jean-Pierre; Bonnet, Francis; Mainardi, Jean-Luc; Arlet, Guillaume; Fartoukh, Muriel; Gallah, Salah; Quesnel, Christophe

2017-06-28

Rapid diagnostic tests detecting microbial resistance are needed for limiting the duration of inappropriateness of empirical antimicrobial therapy (EAT) in intensive care unit patients, besides reducing the use of broad-spectrum antibiotics. We hypothesized that the betaLACTA® test (BLT) could lead to early increase in the adequacy of antimicrobial therapy. This was a case-control study. Sixty-one patients with BLT-guided adaptation of EAT were prospectively included, and then matched with 61 "controls" having similar infection characteristics (community or hospital-acquired, and source of infection), in whom EAT was conventionally adapted to antibiogram results. Endpoints were to compare the proportion of appropriate (primary endpoint) and optimal (secondary endpoint) antimicrobial therapies with each of the two strategies, once microbiological sample culture results were available. Characteristics of patients, infections and EAT at inclusion were similar between groups. Nine early escalations of EAT occurred in the BLT-guided adaptation group, reaching 98% appropriateness vs. 77% in the conventional adaptation group (p < 0.01). The BLT reduced the time until escalation of an inappropriate EAT from 50.5 (48-73) to 27 (24-28) hours (p < 0.01). Seventeen early de-escalations occurred in the BLT-guided adaptation group, compared to one in the conventional adaptation group, reducing patients' exposure to broad-spectrum beta-lactam such as carbapenems. In multivariate analysis, use of the BLT was strongly associated with early appropriate (OR = 18 (3.4-333.8), p = 0.006) and optimal (OR = 35.5 (9.6-231.9), p < 0.001) antimicrobial therapies. Safety parameters were similar between groups. Our study suggests that a BLT-guided adaptation strategy may allow early beta-lactam adaptation from the first 24 hours following the beginning of sepsis management.

Finite-Time Stabilization and Adaptive Control of Memristor-Based Delayed Neural Networks.

PubMed

Wang, Leimin; Shen, Yi; Zhang, Guodong

Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.

Launch Control Systems: Moving Towards a Scalable, Universal Platform for Future Space Endeavors

NASA Technical Reports Server (NTRS)

Sun, Jonathan

2011-01-01

The redirection of NASA away from the Constellation program calls for heavy reliance on commercial launch vehicles for the near future in order to reduce costs and shift focus to research and long term space exploration. To support them, NASA will renovate Kennedy Space Center's launch facilities and make them available for commercial use. However, NASA's current launch software is deeply connected with the now-retired Space Shuttle and is otherwise not massively compatible. Therefore, a new Launch Control System must be designed that is adaptable to a variety of different launch protocols and vehicles. This paper exposits some of the features and advantages of the new system both from the perspective of the software developers and the launch engineers.

Bit-error rate for free-space adaptive optics laser communications.

PubMed

Tyson, Robert K

2002-04-01

An analysis of adaptive optics compensation for atmospheric-turbulence-induced scintillation is presented with the figure of merit being the laser communications bit-error rate. The formulation covers weak, moderate, and strong turbulence; on-off keying; and amplitude-shift keying, over horizontal propagation paths or on a ground-to-space uplink or downlink. The theory shows that under some circumstances the bit-error rate can be improved by a few orders of magnitude with the addition of adaptive optics to compensate for the scintillation. Low-order compensation (less than 40 Zernike modes) appears to be feasible as well as beneficial for reducing the bit-error rate and increasing the throughput of the communication link.

On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\\infty}$ Control.

PubMed

Wang, Ding; Mu, Chaoxu; Liu, Derong; Ma, Hongwen

2018-04-01

In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.

The Researching on Evaluation of Automatic Voltage Control Based on Improved Zoning Methodology

NASA Astrophysics Data System (ADS)

Xiao-jun, ZHU; Ang, FU; Guang-de, DONG; Rui-miao, WANG; De-fen, ZHU

2018-03-01

According to the present serious phenomenon of increasing size and structure of power system, hierarchically structured automatic voltage control(AVC) has been the researching spot. In the paper, the reduced control model is built and the adaptive reduced control model is researched to improve the voltage control effect. The theories of HCSD, HCVS, SKC and FCM are introduced and the effect on coordinated voltage regulation caused by different zoning methodologies is also researched. The generic framework for evaluating performance of coordinated voltage regulation is built. Finally, the IEEE-96 stsyem is used to divide the network. The 2383-bus Polish system is built to verify that the selection of a zoning methodology affects not only the coordinated voltage regulation operation, but also its robustness to erroneous data and proposes a comprehensive generic framework for evaluating its performance. The New England 39-bus network is used to verify the adaptive reduced control models’ performance.

Mammalian phospholipid homeostasis: evidence that membrane curvature elastic stress drives homeoviscous adaptation in vivo

PubMed Central

2016-01-01

Several theories of phospholipid homeostasis have postulated that cells regulate the molecular composition of their bilayer membranes, such that a common biophysical membrane parameter is under homeostatic control. Two commonly cited theories are the intrinsic curvature hypothesis, which states that cells control membrane curvature elastic stress, and the theory of homeoviscous adaptation, which postulates cells control acyl chain packing order (membrane order). In this paper, we present evidence from data-driven modelling studies that these two theories correlate in vivo. We estimate the curvature elastic stress of mammalian cells to be 4–7 × 10−12 N, a value high enough to suggest that in mammalian cells the preservation of membrane order arises through a mechanism where membrane curvature elastic stress is controlled. These results emerge from analysing the molecular contribution of individual phospholipids to both membrane order and curvature elastic stress in nearly 500 cellular compositionally diverse lipidomes. Our model suggests that the de novo synthesis of lipids is the dominant mechanism by which cells control curvature elastic stress and hence membrane order in vivo. These results also suggest that cells can increase membrane curvature elastic stress disproportionately to membrane order by incorporating polyunsaturated fatty acids into lipids. PMID:27534697

Mammalian phospholipid homeostasis: evidence that membrane curvature elastic stress drives homeoviscous adaptation in vivo.

PubMed

Dymond, Marcus K

2016-08-01

Several theories of phospholipid homeostasis have postulated that cells regulate the molecular composition of their bilayer membranes, such that a common biophysical membrane parameter is under homeostatic control. Two commonly cited theories are the intrinsic curvature hypothesis, which states that cells control membrane curvature elastic stress, and the theory of homeoviscous adaptation, which postulates cells control acyl chain packing order (membrane order). In this paper, we present evidence from data-driven modelling studies that these two theories correlate in vivo. We estimate the curvature elastic stress of mammalian cells to be 4-7 × 10(-12) N, a value high enough to suggest that in mammalian cells the preservation of membrane order arises through a mechanism where membrane curvature elastic stress is controlled. These results emerge from analysing the molecular contribution of individual phospholipids to both membrane order and curvature elastic stress in nearly 500 cellular compositionally diverse lipidomes. Our model suggests that the de novo synthesis of lipids is the dominant mechanism by which cells control curvature elastic stress and hence membrane order in vivo These results also suggest that cells can increase membrane curvature elastic stress disproportionately to membrane order by incorporating polyunsaturated fatty acids into lipids. © 2016 The Author(s).

Adaptation of hidden Markov models for recognizing speech of reduced frame rate.

PubMed

Lee, Lee-Min; Jean, Fu-Rong

2013-12-01

The frame rate of the observation sequence in distributed speech recognition applications may be reduced to suit a resource-limited front-end device. In order to use models trained using full-frame-rate data in the recognition of reduced frame-rate (RFR) data, we propose a method for adapting the transition probabilities of hidden Markov models (HMMs) to match the frame rate of the observation. Experiments on the recognition of clean and noisy connected digits are conducted to evaluate the proposed method. Experimental results show that the proposed method can effectively compensate for the frame-rate mismatch between the training and the test data. Using our adapted model to recognize the RFR speech data, one can significantly reduce the computation time and achieve the same level of accuracy as that of a method, which restores the frame rate using data interpolation.

Adaptive servo ventilation for central sleep apnoea in heart failure: SERVE-HF on-treatment analysis.

PubMed

Woehrle, Holger; Cowie, Martin R; Eulenburg, Christine; Suling, Anna; Angermann, Christiane; d'Ortho, Marie-Pia; Erdmann, Erland; Levy, Patrick; Simonds, Anita K; Somers, Virend K; Zannad, Faiez; Teschler, Helmut; Wegscheider, Karl

2017-08-01

This on-treatment analysis was conducted to facilitate understanding of mechanisms underlying the increased risk of all-cause and cardiovascular mortality in heart failure patients with reduced ejection fraction and predominant central sleep apnoea randomised to adaptive servo ventilation versus the control group in the SERVE-HF trial.Time-dependent on-treatment analyses were conducted (unadjusted and adjusted for predictive covariates). A comprehensive, time-dependent model was developed to correct for asymmetric selection effects (to minimise bias).The comprehensive model showed increased cardiovascular death hazard ratios during adaptive servo ventilation usage periods, slightly lower than those in the SERVE-HF intention-to-treat analysis. Self-selection bias was evident. Patients randomised to adaptive servo ventilation who crossed over to the control group were at higher risk of cardiovascular death than controls, while control patients with crossover to adaptive servo ventilation showed a trend towards lower risk of cardiovascular death than patients randomised to adaptive servo ventilation. Cardiovascular risk did not increase as nightly adaptive servo ventilation usage increased.On-treatment analysis showed similar results to the SERVE-HF intention-to-treat analysis, with an increased risk of cardiovascular death in heart failure with reduced ejection fraction patients with predominant central sleep apnoea treated with adaptive servo ventilation. Bias is inevitable and needs to be taken into account in any kind of on-treatment analysis in positive airway pressure studies. Copyright ©ERS 2017.

A Robust Design Methodology for Optimal Microscale Secondary Flow Control in Compact Inlet Diffusers

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Keller, Dennis J.

2001-01-01

It is the purpose of this study to develop an economical Robust design methodology for microscale secondary flow control in compact inlet diffusers. To illustrate the potential of economical Robust Design methodology, two different mission strategies were considered for the subject inlet, namely Maximum Performance and Maximum HCF Life Expectancy. The Maximum Performance mission maximized total pressure recovery while the Maximum HCF Life Expectancy mission minimized the mean of the first five Fourier harmonic amplitudes, i.e., 'collectively' reduced all the harmonic 1/2 amplitudes of engine face distortion. Each of the mission strategies was subject to a low engine face distortion constraint, i.e., DC60<0.10, which is a level acceptable for commercial engines. For each of these missions strategies, an 'Optimal Robust' (open loop control) and an 'Optimal Adaptive' (closed loop control) installation was designed over a twenty degree angle-of-incidence range. The Optimal Robust installation used economical Robust Design methodology to arrive at a single design which operated over the entire angle-of-incident range (open loop control). The Optimal Adaptive installation optimized all the design parameters at each angle-of-incidence. Thus, the Optimal Adaptive installation would require a closed loop control system to sense a proper signal for each effector and modify that effector device, whether mechanical or fluidic, for optimal inlet performance. In general, the performance differences between the Optimal Adaptive and Optimal Robust installation designs were found to be marginal. This suggests, however, that Optimal Robust open loop installation designs can be very competitive with Optimal Adaptive close loop designs. Secondary flow control in inlets is inherently robust, provided it is optimally designed. Therefore, the new methodology presented in this paper, combined array 'Lower Order' approach to Robust DOE, offers the aerodynamicist a very viable and economical way of exploring the concept of Robust inlet design, where the mission variables are brought directly into the inlet design process and insensitivity or robustness to the mission variables becomes a design objective.

Defense Profiles in Adaptation Process to Sport Competition and Their Relationships with Coping, Stress and Control

PubMed Central

Nicolas, Michel; Martinent, Guillaume; Drapeau, Martin; Chahraoui, Khadija; Vacher, Philippe; de Roten, Yves

2017-01-01

The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control) and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six (N = 296) athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles) of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports. PMID:29312070

Defense Profiles in Adaptation Process to Sport Competition and Their Relationships with Coping, Stress and Control.

PubMed

Nicolas, Michel; Martinent, Guillaume; Drapeau, Martin; Chahraoui, Khadija; Vacher, Philippe; de Roten, Yves

2017-01-01

The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control) and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six ( N = 296) athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles) of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports.

The experimental results of a self tuning adaptive controller using online frequency identification. [for Galileo spacecraft

NASA Technical Reports Server (NTRS)

Chiang, W.-W.; Cannon, R. H., Jr.

1985-01-01

A fourth-order laboratory dynamic system featuring very low structural damping and a noncolocated actuator-sensor pair has been used to test a novel real-time adaptive controller, implemented in a minicomputer, which consists of a state estimator, a set of state feedback gains, and a frequency-locked loop for real-time parameter identification. The adaptation algorithm employed can correct controller error and stabilize the system for more than 50 percent variation in the plant's natural frequency, compared with a 10 percent stability margin in frequency variation for a fixed gain controller having the same performance as the nominal plant condition. The very rapid convergence achievable by this adaptive system is demonstrated experimentally, and proven with simple, root-locus methods.

Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don

2003-01-01

This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Technical Reports Server (NTRS)

Wada, Ben K. (Editor); Fanson, James L. (Editor); Miura, Koryo (Editor)

1991-01-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Autonomous atmospheric entry on mars: Performance improvement using a novel adaptive control algorithm

NASA Astrophysics Data System (ADS)

Ulrich, Steve; de Lafontaine, Jean

2007-12-01

Upcoming landing missions to Mars will require on-board guidance and control systems in order to meet the scientific requirement of landing safely within hundreds of meters to the target of interest. More specifically, in the longitudinal plane, the first objective of the entry guidance and control system is to bring the vehicle to its specified velocity at the specified altitude (as required for safe parachute deployment), while the second objective is to reach the target position in the longitudinal plane. This paper proposes an improvement to the robustness of the constant flight path angle guidance law for achieving the first objective. The improvement consists of combining this guidance law with a novel adaptive control scheme, derived from the so-called Simple Adaptive Control (SAC) technique. Monte-Carlo simulation results are shown to demonstrate the accuracy and the robustness of the proposed guidance and adaptive control system.

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Astrophysics Data System (ADS)

Wada, Ben K.; Fanson, James L.; Miura, Koryo

1991-11-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

PubMed Central

Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

2016-01-01

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

PubMed

Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

2016-09-07

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton.

PubMed

Koller, Jeffrey R; Jacobs, Daniel A; Ferris, Daniel P; Remy, C David

2015-11-04

Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, these controllers have relied on a constant gain to map user's muscle activity to actuation control signals. A constant gain may act as a constraint on the user, so we designed a controller that dynamically adapts the gain to the user's myoelectric amplitude. We hypothesized that an adaptive gain proportional myoelectric controller would reduce metabolic energy expenditure compared to walking with the ankle exoskeleton unpowered because users could choose their preferred control gain. We tested eight healthy subjects walking with the adaptive gain proportional myoelectric controller with bilateral ankle exoskeletons. The adaptive gain was updated each stride such that on average the user's peak muscle activity was mapped to maximal power output of the exoskeleton. All subjects participated in three identical training sessions where they walked on a treadmill for 50 minutes (30 minutes of which the exoskeleton was powered) at 1.2 ms(-1). We calculated and analyzed metabolic energy consumption, muscle recruitment, inverse kinematics, inverse dynamics, and exoskeleton mechanics. Using our controller, subjects achieved a metabolic reduction similar to that seen in previous work in about a third of the training time. The resulting controller gain was lower than that seen in previous work (β=1.50±0.14 versus a constant β=2). The adapted gain allowed users more total ankle joint power than that of unassisted walking, increasing ankle power in exchange for a decrease in hip power. Our findings indicate that humans prefer to walk with greater ankle mechanical power output than their unassisted gait when provided with an ankle exoskeleton using an adaptive controller. This suggests that robotic assistance from an exoskeleton can allow humans to adopt gait patterns different from their normal choices for locomotion. In our specific experiment, subjects increased ankle power and decreased hip power to walk with a reduction in metabolic cost. Future exoskeleton devices that rely on proportional myolectric control are likely to demonstrate improved performance by including an adaptive gain.

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

NASA Technical Reports Server (NTRS)

Pavlock, Kate M.

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration, experiment functionality, overall risk mitigation, flight test approach and results, and lessons learned of adaptive controls research of the Full-Scale Advanced Systems Testbed.

Self-Tuning Adaptive-Controller Using Online Frequency Identification

NASA Technical Reports Server (NTRS)

Chiang, W. W.; Cannon, R. H., Jr.

1985-01-01

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Active impulsive noise control using maximum correntropy with adaptive kernel size

NASA Astrophysics Data System (ADS)

Lu, Lu; Zhao, Haiquan

2017-03-01

The active noise control (ANC) based on the principle of superposition is an attractive method to attenuate the noise signals. However, the impulsive noise in the ANC systems will degrade the performance of the controller. In this paper, a filtered-x recursive maximum correntropy (FxRMC) algorithm is proposed based on the maximum correntropy criterion (MCC) to reduce the effect of outliers. The proposed FxRMC algorithm does not requires any priori information of the noise characteristics and outperforms the filtered-x least mean square (FxLMS) algorithm for impulsive noise. Meanwhile, in order to adjust the kernel size of FxRMC algorithm online, a recursive approach is proposed through taking into account the past estimates of error signals over a sliding window. Simulation and experimental results in the context of active impulsive noise control demonstrate that the proposed algorithms achieve much better performance than the existing algorithms in various noise environments.

Suppression of the noise-induced effects in an electrostatic micro-plate using an adaptive back-stepping sliding mode control.

PubMed

Nwagoum Tuwa, Peguy Roussel; Woafo, P

2018-01-01

In this work, an adaptive backstepping sliding mode control approach is applied through the piezoelectric layer in order to control and to stabilize an electrostatic micro-plate. The mathematical model of the system by taking into account the small fluctuations in the gap considered as bounded noise is carried out. The accuracy of the proposed modal equation is proven using the method of lines. By using both approaches, the effects of noise are presented. It is found that they lead to pull-in instability as well as to random chaos. A suitable backstepping approach to improve the tracking performance is integrated to the adaptive sliding mode control in order to eliminate chattering phenomena and reinforce the robustness of the system in presence of uncertainties and external random disturbances. It is proved that all the variables of the closed-loop system are bounded and the system can follow the given reference signals as close as possible. Numerical simulations are provided to show the effectiveness of proposed controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Applications of active adaptive noise control to jet engines

NASA Technical Reports Server (NTRS)

Shoureshi, Rahmat; Brackney, Larry

1993-01-01

During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

Vibration control in statically indeterminate adaptive truss structures

NASA Technical Reports Server (NTRS)

Baycan, C. M.; Utku, Senol; Wada, Ben K.

1993-01-01

In this work vibration control of statically indeterminate adaptive truss structures is investigated. Here, the actuators (i.e., length adjusting devices) that are used for vibration control, work against the axial forces caused by the inertial forces. In statically determinate adaptive trusses no axial force is induced by the actuation. The control problem in statically indeterminate trusses may be dominated by the actuation-induced axial element forces. The creation of actuation-induced axial forces puts the system to a higher energy state, thus aggravates the controls. It is shown that by the usage of sufficient number of slave actuators in addition to the actual control actuators, the actuation-induced axial element forces can be nullified, and the control problem of the statically indeterminate adaptive truss problem is reduced to that of a statically determinate one. It is also shown that the usage of slave actuators saves a great amount of control energy and provides robustness for the controls.

Adaptive management of rangeland systems

USGS Publications Warehouse

Allen, Craig R.; Angeler, David G.; Fontaine, Joseph J.; Garmestani, Ahjond S.; Hart, Noelle M.; Pope, Kevin L.; Twidwell, Dirac

2017-01-01

Adaptive management is an approach to natural resource management that uses structured learning to reduce uncertainties for the improvement of management over time. The origins of adaptive management are linked to ideas of resilience theory and complex systems. Rangeland management is particularly well suited for the application of adaptive management, having sufficient controllability and reducible uncertainties. Adaptive management applies the tools of structured decision making and requires monitoring, evaluation, and adjustment of management. Adaptive governance, involving sharing of power and knowledge among relevant stakeholders, is often required to address conflict situations. Natural resource laws and regulations can present a barrier to adaptive management when requirements for legal certainty are met with environmental uncertainty. However, adaptive management is possible, as illustrated by two cases presented in this chapter. Despite challenges and limitations, when applied appropriately adaptive management leads to improved management through structured learning, and rangeland management is an area in which adaptive management shows promise and should be further explored.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

PubMed

Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

2018-04-01

To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional myoelectric contexts are discussed.

Finite Element Analysis of Folded Airbag in Frontal Impact of Adapted Vehicles for Disabled Drivers

NASA Astrophysics Data System (ADS)

Masiá, J.; Eixerés, B.; Dols, J. F.; Esquerdo, T. V.

2009-11-01

The car control adaptations are used in vehicles in order to facilitate the driving to persons with physical handicaps. This does not have to suppose a decrease of the passive safety that is required to the vehicles. In order to analyze this relation there will be characterized the different control adaptations that are in use together with the different devices of passive safety that can be mounted in the vehicles in diverse cases of impact in order to generate models of simulation. The methodology used to generate this simulation consists of the first phase in which there develops the three-dimensional model of the driving place. For it, there has been used a commercial software of three-dimensional design. Once realized this one divides, the model is imported to the finite elements software in which meshing is generated. Finally, dynamic simulation software is used to assign the most important characteristics like material properties, contact interfaces, gas expansion models, airbag fold types, etc.

Large-scale 3D geoelectromagnetic modeling using parallel adaptive high-order finite element method

DOE PAGES

Grayver, Alexander V.; Kolev, Tzanio V.

2015-11-01

Here, we have investigated the use of the adaptive high-order finite-element method (FEM) for geoelectromagnetic modeling. Because high-order FEM is challenging from the numerical and computational points of view, most published finite-element studies in geoelectromagnetics use the lowest order formulation. Solution of the resulting large system of linear equations poses the main practical challenge. We have developed a fully parallel and distributed robust and scalable linear solver based on the optimal block-diagonal and auxiliary space preconditioners. The solver was found to be efficient for high finite element orders, unstructured and nonconforming locally refined meshes, a wide range of frequencies, largemore » conductivity contrasts, and number of degrees of freedom (DoFs). Furthermore, the presented linear solver is in essence algebraic; i.e., it acts on the matrix-vector level and thus requires no information about the discretization, boundary conditions, or physical source used, making it readily efficient for a wide range of electromagnetic modeling problems. To get accurate solutions at reduced computational cost, we have also implemented goal-oriented adaptive mesh refinement. The numerical tests indicated that if highly accurate modeling results were required, the high-order FEM in combination with the goal-oriented local mesh refinement required less computational time and DoFs than the lowest order adaptive FEM.« less

Large-scale 3D geoelectromagnetic modeling using parallel adaptive high-order finite element method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grayver, Alexander V.; Kolev, Tzanio V.

Here, we have investigated the use of the adaptive high-order finite-element method (FEM) for geoelectromagnetic modeling. Because high-order FEM is challenging from the numerical and computational points of view, most published finite-element studies in geoelectromagnetics use the lowest order formulation. Solution of the resulting large system of linear equations poses the main practical challenge. We have developed a fully parallel and distributed robust and scalable linear solver based on the optimal block-diagonal and auxiliary space preconditioners. The solver was found to be efficient for high finite element orders, unstructured and nonconforming locally refined meshes, a wide range of frequencies, largemore » conductivity contrasts, and number of degrees of freedom (DoFs). Furthermore, the presented linear solver is in essence algebraic; i.e., it acts on the matrix-vector level and thus requires no information about the discretization, boundary conditions, or physical source used, making it readily efficient for a wide range of electromagnetic modeling problems. To get accurate solutions at reduced computational cost, we have also implemented goal-oriented adaptive mesh refinement. The numerical tests indicated that if highly accurate modeling results were required, the high-order FEM in combination with the goal-oriented local mesh refinement required less computational time and DoFs than the lowest order adaptive FEM.« less

Image sensor system with bio-inspired efficient coding and adaptation.

PubMed

Okuno, Hirotsugu; Yagi, Tetsuya

2012-08-01

We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

Mindful Climate Action: Health and Environmental Co-Benefits from Mindfulness-Based Behavioral Training

PubMed Central

Barrett, Bruce; Grabow, Maggie; Middlecamp, Cathy; Mooney, Margaret; Checovich, Mary M.; Converse, Alexander K.; Gillespie, Bob; Yates, Julia

2016-01-01

Greenhouse gases from human activities are causing climate change, creating risks for people around the globe. Behaviors involving transportation, diet, energy use, and purchasing drive greenhouse gas emissions, but are also related to health and well-being, providing opportunity for co-benefits. Replacing shorter automobile trips with walking or cycling, or eating plants rather than animals, for example, may increase personal health, while also reducing environmental impact. Mindfulness-based practices have been shown to enhance a variety of health outcomes, but have not been adapted towards environmental purposes. We designed the Mindful Climate Action (MCA) curriculum to help people improve their health while simultaneously lowering their carbon footprints. Combining mindfulness-based practices with the Stages of Change theory, the MCA program aims to: (1) improve personal health and well-being; (2) decrease energy use; (3) reduce automobile use; (4) increase active transport; (5) shift diet towards plant-based foods; and (6) reduce unnecessary purchasing. Mindfulness practices will foster attentional awareness, openness, and response flexibility, supporting positive behavior change. We plan to test MCA in a randomized controlled trial, with rigorous assessment of targeted outcomes. Our long-term goal is to refine and adapt the MCA program to a variety of audiences, in order to enhance public health and environmental sustainability. PMID:28008371

Reverse time migration by Krylov subspace reduced order modeling

NASA Astrophysics Data System (ADS)

Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

Effects of cognitive control training on the dynamics of (mal)adaptive emotion regulation in daily life.

PubMed

Hoorelbeke, Kristof; Koster, Ernst H W; Demeyer, Ineke; Loeys, Tom; Vanderhasselt, Marie-Anne

2016-10-01

Cognitive control plays a key role in both adaptive emotion regulation, such as positive reappraisal, and maladaptive emotion regulation, such as rumination, with both strategies playing a major role in resilience and well-being. As a result, cognitive control training (CCT) targeting working memory functioning may have the potential to reduce maladaptive emotion regulation and increase adaptive emotion regulation. The current study explored the effects of CCT on positive reappraisal ability in a lab context, and deployment and efficacy of positive appraisal and rumination in daily life. A sample of undergraduates (n = 83) was allocated to CCT or an active control condition, performing 10 online training sessions over a period of 14 days. Effects on regulation of affective states in daily life were assessed using experience sampling over a 7-day posttraining period. Results revealed a positive association between baseline cognitive control and self-reported use of adaptive emotion regulation strategies, whereas maladaptive emotion regulation strategies showed a negative association. CCT showed transfer to working memory functioning on the dual n-back task. Overall, effects of CCT on emotion regulation were limited to reducing deployment of rumination in low positive affective states. However, we did not find beneficial effects on indicators of adaptive emotion regulation. These findings are in line with previous studies targeting maladaptive emotion regulation but suggest limited use in enhancing adaptive emotion regulation in a healthy sample. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Adaptation of water resource systems to an uncertain future

NASA Astrophysics Data System (ADS)

Walsh, Claire L.; Blenkinsop, Stephen; Fowler, Hayley J.; Burton, Aidan; Dawson, Richard J.; Glenis, Vassilis; Manning, Lucy J.; Jahanshahi, Golnaz; Kilsby, Chris G.

2016-05-01

Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth, and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local-scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames Basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth, the median number of drought order occurrences may increase 5-fold by the 2050s. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. A decrease in per capita demand of 3.75 % reduces the median frequency of drought order measures by 50 % by the 2020s. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence, a portfolio of measures is required.

Orthonormal filters for identification in active control systems

NASA Astrophysics Data System (ADS)

Mayer, Dirk

2015-12-01

Many active noise and vibration control systems require models of the control paths. When the controlled system changes slightly over time, adaptive digital filters for the identification of the models are useful. This paper aims at the investigation of a special class of adaptive digital filters: orthonormal filter banks possess the robust and simple adaptation of the widely applied finite impulse response (FIR) filters, but at a lower model order, which is important when considering implementation on embedded systems. However, the filter banks require prior knowledge about the resonance frequencies and damping of the structure. This knowledge can be supposed to be of limited precision, since in many practical systems, uncertainties in the structural parameters exist. In this work, a procedure using a number of training systems to find the fixed parameters for the filter banks is applied. The effect of uncertainties in the prior knowledge on the model error is examined both with a basic example and in an experiment. Furthermore, the possibilities to compensate for the imprecise prior knowledge by a higher filter order are investigated. Also comparisons with FIR filters are implemented in order to assess the possible advantages of the orthonormal filter banks. Numerical and experimental investigations show that significantly lower computational effort can be reached by the filter banks under certain conditions.

Efficacy of Neoseiulus californicus and Phytoseiulus persimilis in suppression of Tetranychus urticae in young clementine plants.

PubMed

Abad-Moyano, Raquel; Pina, Tatiana; Pérez-Panadés, Jordi; Carbonell, Emilio A; Urbaneja, Alberto

2010-04-01

Tetranychus urticae is one of the most damaging tetranychid mites affecting clementine orchards in Spain, where natural control is insufficient. Furthermore, in clementine nurseries, tender foliage is highly susceptible to attack and natural enemies are almost always absent. Therefore, acaricides are often used indiscriminately. Alternative control measures are necessary, both in commercial orchards and clementine nurseries. In order to assess the efficacy of inoculative releases of N. californicus and P. persimilis to reduce T. urticae populations in young Spanish clementine plants, a semi-field experiment was conducted and repeated in three seasons (spring, summer and autumn). Phytoseiulus persimilis was highly effective in reducing both T. urticae infestations and the damage level inflicted on plants at both release rates evaluated (40 and 80 phytoseiids/plant) and all three periods considered. By contrast, N. californicus demonstrated low performance under certain conditions. The results of this study could be adapted and transferred to nurseries and young citrus plantations.

Mechanics of pressure-adaptive honeycomb and its application to wing morphing

NASA Astrophysics Data System (ADS)

Vos, Roelof; Barrett, Ron

2011-09-01

Current, highly active classes of adaptive materials have been considered for use in many different aerospace applications. From adaptive flight control surfaces to wing surfaces, shape-memory alloy (SMA), piezoelectric and electrorheological fluids are making their way into wings, stabilizers and rotor blades. Despite the benefits which can be seen in many classes of aircraft, some profound challenges are ever present, including low power and energy density, high power consumption, high development and installation costs and outright programmatic blockages due to a lack of a materials certification database on FAR 23/25 and 27/29 certified aircraft. Three years ago, a class of adaptive structure was developed to skirt these daunting challenges. This pressure-adaptive honeycomb (PAH) is capable of extremely high performance and is FAA/EASA certifiable because it employs well characterized materials arranged in ways that lend a high level of adaptivity to the structure. This study is centered on laying out the mechanics, analytical models and experimental test data describing this new form of adaptive material. A directionally biased PAH system using an external (spring) force acting on the PAH bending structure was examined. The paper discusses the mechanics of pressure adaptive honeycomb and describes a simple reduced order model that can be used to simplify the geometric model in a finite element environment. The model assumes that a variable stiffness honeycomb results in an overall deformation of the honeycomb. Strains in excess of 50% can be generated through this mechanism without encountering local material (yield) limits. It was also shown that the energy density of pressure-adaptive honeycomb is akin to that of shape-memory alloy, while exhibiting strains that are an order of magnitude greater with an energy efficiency close to 100%. Excellent correlation between theory and experiment is demonstrated in a number of tests. A proof-of-concept wing section test was conducted on a 12% thick wing section representative of a modern commercial aircraft winglet or flight control surface with a 35% PAH trailing edge. It was shown that camber variations in excess of 5% can be generated by a pressure differential of 40 kPa. Results of subsequent wind tunnel test show an increase in lift coefficient of 0.3 at 23 m s - 1 through an angle of attack from - 6° to + 20°. This paper was originally presented at the 2010 ASME SMASIS conference, as paper 'SMASIS 2010-3634'. Despite the substantial changes that have been made to the paper, there are still various figures and text stemming from the original.

Full-order Luenberger observer based on fuzzy-logic control for sensorless field-oriented control of a single-sided linear induction motor.

PubMed

Holakooie, Mohammad Hosein; Ojaghi, Mansour; Taheri, Asghar

2016-01-01

This paper investigates sensorless indirect field oriented control (IFOC) of SLIM with full-order Luenberger observer. The dynamic equations of SLIM are first elaborated to draw full-order Luenberger observer with some simplifying assumption. The observer gain matrix is derived from conventional procedure so that observer poles are proportional to SLIM poles to ensure the stability of system for wide range of linear speed. The operation of observer is significantly impressed by adaptive scheme. A fuzzy logic control (FLC) is proposed as adaptive scheme to estimate linear speed using speed tuning signal. The parameters of FLC are tuned using an off-line method through chaotic optimization algorithm (COA). The performance of the proposed observer is verified by both numerical simulation and real-time hardware-in-the-loop (HIL) implementation. Moreover, a detailed comparative study among proposed and other speed observers is obtained under different operation conditions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach.

PubMed

Silva, Pedro; Matos, Vitor; Santos, Cristina P

2014-02-01

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy-for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot's perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach.

A homotopy algorithm for digital optimal projection control GASD-HADOC

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.

1993-01-01

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum.

PubMed

Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Dean, Paul; Anderson, Sean R; Porrill, John

2015-01-01

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

A Conditional Exposure Control Method for Multidimensional Adaptive Testing

ERIC Educational Resources Information Center

Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A.

2009-01-01

In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…

Implicit adaptive mesh refinement for 2D reduced resistive magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Philip, Bobby; Chacón, Luis; Pernice, Michael

2008-10-01

An implicit structured adaptive mesh refinement (SAMR) solver for 2D reduced magnetohydrodynamics (MHD) is described. The time-implicit discretization is able to step over fast normal modes, while the spatial adaptivity resolves thin, dynamically evolving features. A Jacobian-free Newton-Krylov method is used for the nonlinear solver engine. For preconditioning, we have extended the optimal "physics-based" approach developed in [L. Chacón, D.A. Knoll, J.M. Finn, An implicit, nonlinear reduced resistive MHD solver, J. Comput. Phys. 178 (2002) 15-36] (which employed multigrid solver technology in the preconditioner for scalability) to SAMR grids using the well-known Fast Adaptive Composite grid (FAC) method [S. McCormick, Multilevel Adaptive Methods for Partial Differential Equations, SIAM, Philadelphia, PA, 1989]. A grid convergence study demonstrates that the solver performance is independent of the number of grid levels and only depends on the finest resolution considered, and that it scales well with grid refinement. The study of error generation and propagation in our SAMR implementation demonstrates that high-order (cubic) interpolation during regridding, combined with a robustly damping second-order temporal scheme such as BDF2, is required to minimize impact of grid errors at coarse-fine interfaces on the overall error of the computation for this MHD application. We also demonstrate that our implementation features the desired property that the overall numerical error is dependent only on the finest resolution level considered, and not on the base-grid resolution or on the number of refinement levels present during the simulation. We demonstrate the effectiveness of the tool on several challenging problems.

Coordinating IMC-PID and adaptive SMC controllers for a PEMFC.

PubMed

Wang, Guo-Liang; Wang, Yong; Shi, Jun-Hai; Shao, Hui-He

2010-01-01

For a Proton Exchange Membrane Fuel Cell (PEMFC) power plant with a methanol reformer, the process parameters and power output are considered simultaneously to avoid violation of the constraints and to keep the fuel cell power plant safe and effective. In this paper, a novel coordinating scheme is proposed by combining an Internal Model Control (IMC) based PID Control and adaptive Sliding Mode Control (SMC). The IMC-PID controller is designed for the reformer of the fuel flow rate according to the expected first-order dynamic properties. The adaptive SMC controller of the fuel cell current has been designed using the constant plus proportional rate reaching law. The parameters of the SMC controller are adaptively tuned according to the response of the fuel flow rate control system. When the power output controller feeds back the current references to these two controllers, the coordinating controllers system works in a system-wide way. The simulation results of the PEMFC power plant demonstrate the effectiveness of the proposed method. 2009 ISA. Published by Elsevier Ltd. All rights reserved.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Optical Profilometers Using Adaptive Signal Processing

NASA Technical Reports Server (NTRS)

Hall, Gregory A.; Youngquist, Robert; Mikhael, Wasfy

2006-01-01

A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

Adaptive Control System of Hydraulic Pressure Based on The Mathematical Modeling

NASA Astrophysics Data System (ADS)

Pilipenko, A. V.; Pilipenko, A. P.; Kanatnikov, N. V.

2016-04-01

In this paper, the authors highlight the problem of replacing an old heavy industrial equipment, and offer the replacement of obsolete control systems on the modern adaptive control system, which takes into account changes in the hydraulic system of the press and compensates them with a corrective action. The proposed system can reduce a water hammer and thereby increase the durability of the hydraulic system and tools.

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Standing on slopes - how current microprocessor-controlled prosthetic feet support transtibial and transfemoral amputees in an everyday task.

PubMed

Ernst, Michael; Altenburg, Björn; Bellmann, Malte; Schmalz, Thomas

2017-11-16

Conventional prosthetic feet like energy storage and return feet provide only a limited range of ankle motion compared to human ones. In order to overcome the poor rotational adaptability, prosthetic manufacturers developed different prosthetic feet with an additional rotational joint and implemented active control in different states. It was the aim of the study to investigate to what extent these commercially available microprocessor-controlled prosthetic feet support a natural posture while standing on inclines and which concept is most beneficial for lower limb amputees. Four unilateral transtibial and four unilateral transfemoral amputees participated in the study. Each of the subjects wore five different microprocessor-controlled prosthetic feet in addition to their everyday feet. The subjects were asked to stand on slopes of different inclinations (level ground, upward slope of 10°, and downward slope of -10°). Vertical ground reaction forces, joint torques and joint angles in the sagittal plane were measured for both legs separately for the different situations and compared to a non-amputee reference group. Differences in the biomechanical parameters were observed between the different prosthetic feet and compared to the reference group for the investigated situations. They were most prominent while standing on a downward slope. For example, on the prosthetic side, the vertical ground reaction force is reduced by about 20%, and the torque about the knee acts to flex the joint for feet that are not capable of a full adaptation to the downward slope. In contrast, fully adaptable feet with an auto-adaptive dorsiflexion stop show no changes in vertical ground reaction forces and knee extending torques. A prosthetic foot that provides both, an auto-adaptive dorsiflexion stop and a sufficient range of motion for fully adapting to inclinations appears to be the key element in the prosthetic fitting for standing on inclinations in lower limb amputees. In such situations, this prosthetic concept appears superior to both, conventional feet with passive structures as well as feet that solely provide a sufficient range of motion. The results also indicate that both, transfemoral and transtibial amputees benefit from such a foot.

Adaptive kanban control mechanism for a single-stage hybrid system

NASA Astrophysics Data System (ADS)

Korugan, Aybek; Gupta, Surendra M.

2002-02-01

In this paper, we consider a hybrid manufacturing system with two discrete production lines. Here the output of either production line can satisfy the demand for the same type of product without any penalties. The interarrival times for demand occurrences and service completions are exponentially distributed i.i.d. variables. In order to control this type of manufacturing system we suggest a single stage pull type control mechanism with adaptive kanbans and state independent routing of the production information.

Adaptive nonlinear polynomial neural networks for control of boundary layer/structural interaction

NASA Technical Reports Server (NTRS)

Parker, B. Eugene, Jr.; Cellucci, Richard L.; Abbott, Dean W.; Barron, Roger L.; Jordan, Paul R., III; Poor, H. Vincent

1993-01-01

The acoustic pressures developed in a boundary layer can interact with an aircraft panel to induce significant vibration in the panel. Such vibration is undesirable due to the aerodynamic drag and structure-borne cabin noises that result. The overall objective of this work is to develop effective and practical feedback control strategies for actively reducing this flow-induced structural vibration. This report describes the results of initial evaluations using polynomial, neural network-based, feedback control to reduce flow induced vibration in aircraft panels due to turbulent boundary layer/structural interaction. Computer simulations are used to develop and analyze feedback control strategies to reduce vibration in a beam as a first step. The key differences between this work and that going on elsewhere are as follows: that turbulent and transitional boundary layers represent broadband excitation and thus present a more complex stochastic control scenario than that of narrow band (e.g., laminar boundary layer) excitation; and secondly, that the proposed controller structures are adaptive nonlinear infinite impulse response (IIR) polynomial neural network, as opposed to the traditional adaptive linear finite impulse response (FIR) filters used in most studies to date. The controllers implemented in this study achieved vibration attenuation of 27 to 60 dB depending on the type of boundary layer established by laminar, turbulent, and intermittent laminar-to-turbulent transitional flows. Application of multi-input, multi-output, adaptive, nonlinear feedback control of vibration in aircraft panels based on polynomial neural networks appears to be feasible today. Plans are outlined for Phase 2 of this study, which will include extending the theoretical investigation conducted in Phase 2 and verifying the results in a series of laboratory experiments involving both bum and plate models.

Effect of wine-based marinades on the behavior of Salmonella Typhimurium and background flora in beef fillets.

PubMed

Nisiotou, A; Chorianopoulos, N G; Gounadaki, A; Panagou, E Z; Nychas, G-J E

2013-06-17

The aim of this study was to evaluate the wine-based marinades to control the survival of acid-adapted and non-adapted Salmonella Typhimurium and background flora of fresh beef stored aerobically or under modified atmosphere. Beef slices were inoculated with a 3-strain cocktail of acid-adapted or non-adapted Salmonella Typhimurium strains DT 193, 4/74 and DSM 554 and marinated by immersion in wine (W) or wine supplemented with 0.3% thyme essential oil (WEO), for 12h at 4°C. Marinated slices were then stored under air or modified atmosphere conditions at 5°C. S. Typhimurium and background flora were followed for a 19-day period of storage. S. Typhimurium individual strains were monitored by pulsed field gel electrophoresis. Marination with wine significantly (P<0.05) reduced the background flora compared to the control (non-marinated). Furthermore, immersion of fillets in W or WEO marinades for 12h significantly (P<0.05) reduced the levels of S. Typhimurium compared to the non-marinated (control) samples by 1.1 and 1.4logCFU/g or 2.0 and 1.9logCFU/g for acid-adapted and non-adapted cells, respectively. Acid-adapted cells were more susceptible (P<0.05) to the addition of thyme essential oil in the wine marinade. The epidemic multi-drug resistant DT 193, the 4/74 and DSM 554 strains survived marination (for both W and WEO) and were detected at about similar proportions as revealed by PFGE results. Present results indicate that wine-based marinades are efficient, from a safety and shelf life stand point, in reducing pathogen's levels as well as the background beef flora. Copyright © 2013 Elsevier B.V. All rights reserved.

Robustness of reduced-order observer-based controllers in transitional 2D Blasius boundary layers

NASA Astrophysics Data System (ADS)

Belson, Brandt; Semeraro, Onofrio; Rowley, Clarence; Pralits, Jan; Henningson, Dan

2011-11-01

In this work, we seek to delay transition in the Blasius boundary layer. We trip the flow with an upstream disturbance and dampen the growth of the resulting structures downstream. The observer-based controllers use a single sensor and a single localized body force near the wall. To formulate the controllers, we first find a reduced-order model of the system via the Eigensystem Realization Algorithm (ERA), then find the H2 optimal controller for this reduced-order system. We find the resulting controllers are effective only when the sensor is upstream of the actuator (in a feedforward configuration), but as is expected, are sensitive to model uncertainty. When the sensor is downstream of the actuator (in a feedback configuration), the reduced-order observer-based controllers are not robust and ineffective on the full system. In order to investigate the robustness properties of the system, an iterative technique called the adjoint of the direct adjoint (ADA) is employed to find a full-dimensional H2 optimal controller. This avoids the reduced-order modelling step and serves as a reference point. ADA is promising for investigating the lack of robustness previously mentioned.

High shear rate flow in a linear stroke magnetorheological energy absorber

NASA Astrophysics Data System (ADS)

Hu, W.; Wereley, N. M.; Hiemenz, G. J.; Ngatu, G. T.

2014-05-01

To provide adaptive stroking load in the crew seats of ground vehicles to protect crew from blast or impact loads, a magnetorheological energy absorber (MREA) or shock absorber was developed. The MREA provides appropriate levels of controllable stroking load for different occupant weights and peak acceleration because the viscous stroking load generated by the MREA force increases with velocity squared, thereby reducing its controllable range at high piston velocity. Therefore, MREA behavior at high piston velocity is analyzed and validated experimentally in order to investigate the effects of velocity and magnetic field on MREA performance. The analysis used to predict the MREA force as a function of piston velocity squared and applied field is presented. A conical fairing is mounted to the piston head of the MREA in order reduce predicted inlet flow loss by 9% at nominal velocity of 8 m/s, which resulted in a viscous force reduction of nominally 4%. The MREA behavior is experimentally measured using a high speed servo-hydraulic testing system for speeds up to 8 m/s. The measured MREA force is used to validate the analysis, which captures the transient force quite accurately, although the peak force is under-predicted at the peak speed of 8 m/s.

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Johnson, Marcus; Nguyen, Nhan

2011-01-01

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

DHA-fluorescent probe is sensitive to membrane order and reveals molecular adaptation of DHA in ordered lipid microdomains☆

PubMed Central

Teague, Heather; Ross, Ron; Harris, Mitchel; Mitchell, Drake C.; Shaikh, Saame Raza

2012-01-01

Docosahexaenoic acid (DHA) disrupts the size and order of plasma membrane lipid microdomains in vitro and in vivo. However, it is unknown how the highly disordered structure of DHA mechanistically adapts to increase the order of tightly packed lipid microdomains. Therefore, we studied a novel DHA-Bodipy fluorescent probe to address this issue. We first determined if the DHA-Bodipy probe localized to the plasma membrane of primary B and immortal EL4 cells. Image analysis revealed that DHA-Bodipy localized into the plasma membrane of primary B cells more efficiently than EL4 cells. We then determined if the probe detected changes in plasma membrane order. Quantitative analysis of time-lapse movies established that DHA-Bodipy was sensitive to membrane molecular order. This allowed us to investigate how DHA-Bodipy physically adapted to ordered lipid microdomains. To accomplish this, we employed steady-state and time-resolved fluorescence anisotropy measurements in lipid vesicles of varying composition. Similar to cell culture studies, the probe was highly sensitive to membrane order in lipid vesicles. Moreover, these experiments revealed, relative to controls, that upon incorporation into highly ordered microdomains, DHA-Bodipy underwent an increase in its fluorescence lifetime and molecular order. In addition, the probe displayed a significant reduction in its rotational diffusion compared to controls. Altogether, DHA-Bodipy was highly sensitive to membrane order and revealed for the first time that DHA, despite its flexibility, could become ordered with less rotational motion inside ordered lipid microdomains. Mechanistically, this explains how DHA acyl chains can increase order upon formation of lipid microdomains in vivo. PMID:22841541

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics

PubMed Central

Zou, Weiyao; Burns, Stephen A.

2012-01-01

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. PMID:22441462

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics.

PubMed

Zou, Weiyao; Burns, Stephen A

2012-03-20

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. © 2012 Optical Society of America

Continuously Adaptive vs. Discrete Changes of Task Difficulty in the Training of a Complex Perceptual-Motor Task.

ERIC Educational Resources Information Center

Wood, Milton E.

The purpose of the effort was to determine the benefits to be derived from the adaptive training technique of automatically adjusting task difficulty as a function of a student skill during early learning of a complex perceptual motor task. A digital computer provided the task dynamics, scoring, and adaptive control of a second-order, two-axis,…

Dysfunction of Rapid Neural Adaptation in Dyslexia.

PubMed

Perrachione, Tyler K; Del Tufo, Stephanie N; Winter, Rebecca; Murtagh, Jack; Cyr, Abigail; Chang, Patricia; Halverson, Kelly; Ghosh, Satrajit S; Christodoulou, Joanna A; Gabrieli, John D E

2016-12-21

Identification of specific neurophysiological dysfunctions resulting in selective reading difficulty (dyslexia) has remained elusive. In addition to impaired reading development, individuals with dyslexia frequently exhibit behavioral deficits in perceptual adaptation. Here, we assessed neurophysiological adaptation to stimulus repetition in adults and children with dyslexia for a wide variety of stimuli, spoken words, written words, visual objects, and faces. For every stimulus type, individuals with dyslexia exhibited significantly diminished neural adaptation compared to controls in stimulus-specific cortical areas. Better reading skills in adults and children with dyslexia were associated with greater repetition-induced neural adaptation. These results highlight a dysfunction of rapid neural adaptation as a core neurophysiological difference in dyslexia that may underlie impaired reading development. Reduced neurophysiological adaptation may relate to prior reports of reduced behavioral adaptation in dyslexia and may reveal a difference in brain functions that ultimately results in a specific reading impairment. Copyright © 2016 Elsevier Inc. All rights reserved.

Woofer-tweeter adaptive optics scanning laser ophthalmoscopic imaging based on Lagrange-multiplier damped least-squares algorithm.

PubMed

Zou, Weiyao; Qi, Xiaofeng; Burns, Stephen A

2011-07-01

We implemented a Lagrange-multiplier (LM)-based damped least-squares (DLS) control algorithm in a woofer-tweeter dual deformable-mirror (DM) adaptive optics scanning laser ophthalmoscope (AOSLO). The algorithm uses data from a single Shack-Hartmann wavefront sensor to simultaneously correct large-amplitude low-order aberrations by a woofer DM and small-amplitude higher-order aberrations by a tweeter DM. We measured the in vivo performance of high resolution retinal imaging with the dual DM AOSLO. We compared the simultaneous LM-based DLS dual DM controller with both single DM controller, and a successive dual DM controller. We evaluated performance using both wavefront (RMS) and image quality metrics including brightness and power spectrum. The simultaneous LM-based dual DM AO can consistently provide near diffraction-limited in vivo routine imaging of human retina.

Training Maneuver Evaluation for Reduced Order Modeling of Stability & Control Properties Using Computational Fluid Dynamics

DTIC Science & Technology

2013-03-01

reduced order model is created. Finally, previous research in this area of study will be examined, and its application to this research will be...TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF STABILITY & CONTROL PROPERTIES USING COMPUTATIONAL FLUID DYNAMICS THESIS Craig Curtis...Government and is not subject to copyright protection in the United States. AFIT-ENY-13-M-28 TRAINING MANEUVER EVALUATION FOR REDUCED ORDER MODELING OF

A method for obtaining reduced-order control laws for high-order systems using optimization techniques

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Newsom, J. R.; Abel, I.

1981-01-01

A method of synthesizing reduced-order optimal feedback control laws for a high-order system is developed. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean-square steady-state responses and control inputs. An analogy with the linear quadractic Gaussian solution is utilized to select a set of design variables and their initial values. To improve the stability margins of the system, an input-noise adjustment procedure is used in the design algorithm. The method is applied to the synthesis of an active flutter-suppression control law for a wind tunnel model of an aeroelastic wing. The reduced-order controller is compared with the corresponding full-order controller and found to provide nearly optimal performance. The performance of the present method appeared to be superior to that of two other control law order-reduction methods. It is concluded that by using the present algorithm, nearly optimal low-order control laws with good stability margins can be synthesized.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

DOE PAGES

Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...

2015-09-14

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less

Accurate Adaptive Level Set Method and Sharpening Technique for Three Dimensional Deforming Interfaces

NASA Technical Reports Server (NTRS)

Kim, Hyoungin; Liou, Meng-Sing

2011-01-01

In this paper, we demonstrate improved accuracy of the level set method for resolving deforming interfaces by proposing two key elements: (1) accurate level set solutions on adapted Cartesian grids by judiciously choosing interpolation polynomials in regions of different grid levels and (2) enhanced reinitialization by an interface sharpening procedure. The level set equation is solved using a fifth order WENO scheme or a second order central differencing scheme depending on availability of uniform stencils at each grid point. Grid adaptation criteria are determined so that the Hamiltonian functions at nodes adjacent to interfaces are always calculated by the fifth order WENO scheme. This selective usage between the fifth order WENO and second order central differencing schemes is confirmed to give more accurate results compared to those in literature for standard test problems. In order to further improve accuracy especially near thin filaments, we suggest an artificial sharpening method, which is in a similar form with the conventional re-initialization method but utilizes sign of curvature instead of sign of the level set function. Consequently, volume loss due to numerical dissipation on thin filaments is remarkably reduced for the test problems

Process- and controller-adaptations determine the physiological effects of cold acclimation.

PubMed

Werner, Jürgen

2008-09-01

Experimental results on physiological effects of cold adaptation seem confusing and apparently incompatible with one another. This paper will explain that a substantial part of such a variety of results may be deduced from a common functional concept. A core/shell treatment ("model") of the thermoregulatory system is used with mean body temperature as the controlled variable. Adaptation, as a higher control level, is introduced into the system. Due to persistent stressors, either the (heat transfer) process or the controller properties (parameters) are adjusted (or both). It is convenient to call the one "process adaptation" and the other "controller adaptation". The most commonly demonstrated effect of autonomic cold acclimation is a change in the controller threshold. The analysis shows that this necessarily means a lowering of body temperature because of a lowered metabolic rate. This explains experimental results on both Europeans in the climatic chamber and Australian Aborigines in a natural environment. Exclusive autonomic process adaptation occurs in the form of a better insulation. The analysis explains why the post-adaptive steady-state can only be achieved, if the controller system reduces metabolism and why in spite of this the new state is inevitably characterized by a rise in body temperature. If both process and controller adaptations are simultaneously present, there may be not any change of body temperature at all, e.g., as demonstrated in animal experiments. Whether this kind of adaptation delivers a decrease, an increase or no change of mean body temperature, depends on the proportion of process and controller adaptation.

ADAPTIVE CLEARANCE CONTROL SYSTEMS FOR TURBINE ENGINES

NASA Technical Reports Server (NTRS)

Blackwell, Keith M.

2004-01-01

The Controls and Dynamics Technology Branch at NASA Glenn Research Center primarily deals in developing controls, dynamic models, and health management technologies for air and space propulsion systems. During the summer of 2004 I was granted the privilege of working alongside professionals who were developing an active clearance control system for commercial jet engines. Clearance, the gap between the turbine blade tip and the encompassing shroud, increases as a result of wear mechanisms and rubbing of the turbine blades on shroud. Increases in clearance cause larger specific fuel consumption (SFC) and loss of efficient air flow. This occurs because, as clearances increase, the engine must run hotter and bum more fuel to achieve the same thrust. In order to maintain efficiency, reduce fuel bum, and reduce exhaust gas temperature (EGT), the clearance must be accurately controlled to gap sizes no greater than a few hundredths of an inch. To address this problem, NASA Glenn researchers have developed a basic control system with actuators and sensors on each section of the shroud. Instead of having a large uniform metal casing, there would be sections of the shroud with individual sensors attached internally that would move slightly to reform and maintain clearance. The proposed method would ultimately save the airline industry millions of dollars.

Disturbance observer based active and adaptive synchronization of energy resource chaotic system.

PubMed

Wei, Wei; Wang, Meng; Li, Donghai; Zuo, Min; Wang, Xiaoyi

2016-11-01

In this paper, synchronization of a three-dimensional energy resource chaotic system is considered. For the sake of achieving the synchronization between the drive and response systems, two different nonlinear control approaches, i.e. active control with known parameters and adaptive control with unknown parameters, have been designed. In order to guarantee the transient performance, finite-time boundedness (FTB) and finite-time stability (FTS) are introduced in the design of active control and adaptive control, respectively. Simultaneously, in view of the existence of disturbances, a new disturbance observer is proposed to estimate the disturbance. The conditions of the asymptotic stability for the closed-loop system are obtained. Numerical simulations are provided to illustrate the proposed approaches. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear stability and control study of highly maneuverable high performance aircraft, phase 2

NASA Technical Reports Server (NTRS)

Mohler, R. R.

1992-01-01

This research should lead to the development of new nonlinear methodologies for the adaptive control and stability analysis of high angle-of-attack aircraft such as the F18 (HARV). The emphasis has been on nonlinear adaptive control, but associated model development, system identification, stability analysis and simulation is performed in some detail as well. Various models under investigation for different purposes are summarized in tabular form. Models and simulation for the longitudinal dynamics have been developed for all types except the nonlinear ordinary differential equation model. Briefly, studies completed indicate that nonlinear adaptive control can outperform linear adaptive control for rapid maneuvers with large changes in alpha. The transient responses are compared where the desired alpha varies from 5 degrees to 60 degrees to 30 degrees and back to 5 degrees in all about 16 sec. Here, the horizontal stabilator is the only control used with an assumed first-order linear actuator with a 1/30 sec time constant.

Adaptive control of a millimeter-scale flapping-wing robot.

PubMed

Chirarattananon, Pakpong; Ma, Kevin Y; Wood, Robert J

2014-06-01

Challenges for the controlled flight of a robotic insect are due to the inherent instability of the system, complex fluid-structure interactions, and the general lack of a complete system model. In this paper, we propose theoretical models of the system based on the limited information available from previous work and a comprehensive flight controller. The modular flight controller is derived from Lyapunov function candidates with proven stability over a large region of attraction. Moreover, it comprises adaptive components that are capable of coping with uncertainties in the system that arise from manufacturing imperfections. We have demonstrated that the proposed methods enable the robot to achieve sustained hovering flights with relatively small errors compared to a non-adaptive approach. Simple lateral maneuvers and vertical takeoff and landing flights are also shown to illustrate the fidelity of the flight controller. The analysis suggests that the adaptive scheme is crucial in order to achieve millimeter-scale precision in flight control as observed in natural insect flight.

An adaptive human response mechanism controlling the V/STOL aircraft. Appendix 3: The adaptive control model of a pilot in V/STOL aircraft control loops. M.S. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Kucuk, Senol

1988-01-01

Importance of the role of human operator in control systems has led to the particular area of manual control theory. Human describing functions were developed to model human behavior for manual control studies to take advantage of the successful and safe human operations. A single variable approach is presented that can be extended for multi-variable tasks where a low order human response model is used together with its rules, to adapt the model on-line, being capable of responding to the changes in the controlled element dynamics. Basic control theory concepts are used to combine the model, constrained with the physical observations, particularly, for the case of aircraft control. Pilot experience is represented as the initial model parameters. An adaptive root-locus method is presented as the adaptation law of the model where the closed loop bandwidth of the system is to be preserved in a stable manner with the adjustments of the pilot handling qualities which relate the latter to the closed loop bandwidth and damping of the closed loop pilot aircraft combination. A Kalman filter parameter estimator is presented as the controlled element identifier of the adaptive model where any discrepancies of the open loop dynamics from the presented one, are sensed to be compensated.

Adaptation of feedforward movement control is abnormal in patients with cervical dystonia and tremor.

PubMed

Avanzino, Laura; Ravaschio, Andrea; Lagravinese, Giovanna; Bonassi, Gaia; Abbruzzese, Giovanni; Pelosin, Elisa

2018-01-01

It is under debate whether the cerebellum plays a role in dystonia pathophysiology and in the expression of clinical phenotypes. We investigated a typical cerebellar function (anticipatory movement control) in patients with cervical dystonia (CD) with and without tremor. Twenty patients with CD, with and without tremor, and 17 healthy controls were required to catch balls of different load: 15 trials with a light ball, 25 trials with a heavy ball (adaptation) and 15 trials with a light ball (post-adaptation). Arm movements were recorded using a motion capture system. We evaluated: (i) the anticipatory adjustment (just before the impact); (ii) the extent and rate of the adaptation (at the impact) and (iii) the aftereffect in the post-adaptation phase. The anticipatory adjustment was reduced during adaptation in CD patients with tremor respect to CD patients without tremor and controls. The extent and rate of adaptation and the aftereffect in the post-adaptation phase were smaller in CD with tremor than in controls and CD without tremor. Patients with cervical dystonia and tremor display an abnormal predictive movement control. Our findings point to a possible role of cerebellum in the expression of a clinical phenotype in dystonia. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles

NASA Astrophysics Data System (ADS)

Davis, L. C.

2016-06-01

Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested state at the bottleneck. The nature of the congested state, when it occurs, appears to be similar under a variety of conditions. Typically 80-100 vehicles are approximately equally distributed between the lanes in the 500 m region prior to the end of the terminated lane. Without the adaptive cruise control capability, connected vehicles can delay the onset of congestion but do not increase the asymptotic flow past the bottleneck. Calculations are done using the Kerner-Klenov three-phase theory, stochastic discrete-time model for manual vehicles. The dynamics of the connected vehicles is given by a conventional adaptive cruise control algorithm plus commanded deceleration. Because time in the model for manual vehicles is discrete (one-second intervals), it is assumed that the acceleration of any vehicle immediately in front of a connected vehicle is constant during the time interval, thereby preserving the computational simplicity and speed of a discrete-time model.

ER fluid applications to vibration control devices and an adaptive neural-net controller

NASA Astrophysics Data System (ADS)

Morishita, Shin; Ura, Tamaki

1993-07-01

Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

Implementation of a MFAC based position sensorless drive for high speed BLDC motors with nonideal back EMF.

PubMed

Li, Haitao; Ning, Xin; Li, Wenzhuo

2017-03-01

In order to improve the reliability and reduce power consumption of the high speed BLDC motor system, this paper presents a model free adaptive control (MFAC) based position sensorless drive with only a dc-link current sensor. The initial commutation points are obtained by detecting the phase of EMF zero-crossing point and then delaying 30 electrical degrees. According to the commutation error caused by the low pass filter (LPF) and other factors, the relationship between commutation error angle and dc-link current is analyzed, a corresponding MFAC based control method is proposed, and the commutation error can be corrected by the controller in real time. Both the simulation and experimental results show that the proposed correction method can achieve ideal commutation effect within the entire operating speed range. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Research on H2 speed governor for diesel engine of marine power station

NASA Astrophysics Data System (ADS)

Huang, Man-Lei

2007-09-01

The frequency stability of a marine power system is determined by the dynamic characteristic of the diesel engine speed regulation system in a marine power station. In order to reduce the effect of load disturbances and improve the dynamic precision of a diesel engine speed governor, a controller was designed for a diesel engine speed regulation system using H2 control theory. This transforms the specifications of the system into a standard H2 control problem. Firstly, the mathematical model of a diesel engine speed regulation system using an H2 speed governor is presented. To counter external disturbances and model uncertainty, the design of an H2 speed governor rests on the problem of mixed sensitivity. Computer simulation verified that the H2 speed governor improves the dynamic precision of a system and the ability to adapt to load disturbances, thus enhancing the frequency stability of marine power systems.

Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.

PubMed

Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu

2018-04-23

This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.

Synchronizing Data-Bus Messages

NASA Technical Reports Server (NTRS)

Harris, L. H.

1985-01-01

Adapter allows communications among as many as 30 data processors without central bus controller. Adapter improves reliability of multiprocessor system by eliminating point of failure that causes entire system to fail. Scheme prevents data collisions and eliminates nonessential polling, thereby reducing power consumption.

Optimize pollutant emissions through adaptive highway management.

DOT National Transportation Integrated Search

2011-09-01

In this project, we investigated the possibility to reduce green house emission : (mainly CO2) from urban highways by adaptive ramp meter control. QUADSTONE : PARAMICS software was used to build a microscopic traffic model for a 4-lane highway : sect...

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

1990-01-01

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

Reduced Wiener Chaos representation of random fields via basis adaptation and projection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsilifis, Panagiotis, E-mail: tsilifis@usc.edu; Department of Civil Engineering, University of Southern California, Los Angeles, CA 90089; Ghanem, Roger G., E-mail: ghanem@usc.edu

2017-07-15

A new characterization of random fields appearing in physical models is presented that is based on their well-known Homogeneous Chaos expansions. We take advantage of the adaptation capabilities of these expansions where the core idea is to rotate the basis of the underlying Gaussian Hilbert space, in order to achieve reduced functional representations that concentrate the induced probability measure in a lower dimensional subspace. For a smooth family of rotations along the domain of interest, the uncorrelated Gaussian inputs are transformed into a Gaussian process, thus introducing a mesoscale that captures intermediate characteristics of the quantity of interest.

Reduced Wiener Chaos representation of random fields via basis adaptation and projection

NASA Astrophysics Data System (ADS)

Tsilifis, Panagiotis; Ghanem, Roger G.

2017-07-01

A new characterization of random fields appearing in physical models is presented that is based on their well-known Homogeneous Chaos expansions. We take advantage of the adaptation capabilities of these expansions where the core idea is to rotate the basis of the underlying Gaussian Hilbert space, in order to achieve reduced functional representations that concentrate the induced probability measure in a lower dimensional subspace. For a smooth family of rotations along the domain of interest, the uncorrelated Gaussian inputs are transformed into a Gaussian process, thus introducing a mesoscale that captures intermediate characteristics of the quantity of interest.

38 CFR 77.18 - Visits to monitor operations and compliance.

Code of Federal Regulations, 2014 CFR

2014-07-01

... AFFAIRS (CONTINUED) GRANTS FOR ADAPTIVE SPORTS PROGRAMS FOR DISABLED VETERANS AND DISABLED MEMBERS OF THE... times, to make visits to all grantee locations where a grantee is using adaptive sports grant funds in order to review grantee accomplishments and management control systems and to provide such technical...

Simulation of branched serial first-order decay of atrazine and metabolites in adapted and nonadapted soils

USGS Publications Warehouse

Webb, R.M.; Sandstrom, M.W.; Krutz, L.J.; Shaner, D.L.

2011-01-01

In the present study a branched serial first-order decay (BSFOD) model is presented and used to derive transformation rates describing the decay of a common herbicide, atrazine, and its metabolites observed in unsaturated soils adapted to previous atrazine applications and in soils with no history of atrazine applications. Calibration of BSFOD models for soils throughout the country can reduce the uncertainty, relative to that of traditional models, in predicting the fate and transport of pesticides and their metabolites and thus support improved agricultural management schemes for reducing threats to the environment. Results from application of the BSFOD model to better understand the degradation of atrazine supports two previously reported conclusions: atrazine (6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine) and its primary metabolites are less persistent in adapted soils than in nonadapted soils; and hydroxyatrazine was the dominant primary metabolite in most of the soils tested. In addition, a method to simulate BSFOD in a one-dimensional solute-transport unsaturated zone model is also presented. ?? 2011 SETAC.

Simulation of branched serial first-order decay of atrazine and metabolites in adapted and nonadapted soils

USGS Publications Warehouse

Webb, Richard M.; Sandstrom, Mark W.; Jason L. Krutz,; Dale L. Shaner,

2011-01-01

In the present study a branched serial first-order decay (BSFOD) model is presented and used to derive transformation rates describing the decay of a common herbicide, atrazine, and its metabolites observed in unsaturated soils adapted to previous atrazine applications and in soils with no history of atrazine applications. Calibration of BSFOD models for soils throughout the country can reduce the uncertainty, relative to that of traditional models, in predicting the fate and transport of pesticides and their metabolites and thus support improved agricultural management schemes for reducing threats to the environment. Results from application of the BSFOD model to better understand the degradation of atrazine supports two previously reported conclusions: atrazine (6-chloro-N-ethyl-N′-(1-methylethyl)-1,3,5-triazine-2,4-diamine) and its primary metabolites are less persistent in adapted soils than in nonadapted soils; and hydroxyatrazine was the dominant primary metabolite in most of the soils tested. In addition, a method to simulate BSFOD in a one-dimensional solute-transport unsaturated zone model is also presented.

A reduced-order adaptive neuro-fuzzy inference system model as a software sensor for rapid estimation of five-day biochemical oxygen demand

NASA Astrophysics Data System (ADS)

Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin

2013-07-01

The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.

Towards feasible and effective predictive wavefront control for adaptive optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poyneer, L A; Veran, J

We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

Development of HIDEC adaptive engine control systems

NASA Technical Reports Server (NTRS)

Landy, R. J.; Yonke, W. A.; Stewart, J. F.

1986-01-01

The purpose of NASA's Highly Integrated Digital Electronic Control (HIDEC) flight research program is the development of integrated flight propulsion control modes, and the evaluation of their benefits aboard an F-15 test aircraft. HIDEC program phases are discussed, with attention to the Adaptive Engine Control System (ADECS I); this involves the upgrading of PW1128 engines for operation at higher engine pressure ratios and the production of greater thrust. ADECS II will involve the development of a constant thrust mode which will significantly reduce turbine operating temperatures.

Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

PubMed

Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

2014-03-01

In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptation to walking with an exoskeleton that assists ankle extension.

PubMed

Galle, S; Malcolm, P; Derave, W; De Clercq, D

2013-07-01

The goal of this study was to investigate adaptation to walking with bilateral ankle-foot exoskeletons with kinematic control that assisted ankle extension during push-off. We hypothesized that subjects would show a neuromotor and metabolic adaptation during a 24min walking trial with a powered exoskeleton. Nine female subjects walked on a treadmill at 1.36±0.04ms(-1) during 24min with a powered exoskeleton and 4min with an unpowered exoskeleton. Subjects showed a metabolic adaptation after 18.5±5.0min, followed by an adapted period. Metabolic cost, electromyography and kinematics were compared between the unpowered condition, the beginning of the adaptation and the adapted period. In the beginning of the adaptation (4min), a reduction in metabolic cost of 9% was found compared to the unpowered condition. This reduction was accompanied by reduced muscular activity in the plantarflexor muscles, as the powered exoskeleton delivered part of the necessary ankle extension moment. During the adaptation this metabolic reduction further increased to 16%, notwithstanding a constant exoskeleton assistance. This increased reduction is the result of a neuromotor adaptation in which subjects adapt to walking with the exoskeleton, thereby reducing muscular activity in all leg muscles. Because of the fast adaptation and the significant reductions in metabolic cost we want to highlight the potential of an ankle-foot exoskeleton with kinematic control that assists ankle extension during push-off. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive method for electron bunch profile prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scheinker, Alexander; Gessner, Spencer

2015-10-01

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial controlmore » system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.« less

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Efficacy of adaptation measures to future water scarcity on a global scale

NASA Astrophysics Data System (ADS)

Yoshikawa, S.; Kanae, S.

2015-12-01

Water supply sources for all sector are critically important for agricultural and industrial productivity. The current rapid increase in water use is considered unsustainable and threatens human life. In our previous study (Yoshikawa et al., 2014 in HESS), we estimated the time-varying dependence of water requirements from water supply sources during past and future periods using the global water resources model, H08. The sources of water requirements were specified using four categories: rivers, large reservoirs, medium-size reservoirs, and non-local non-renewable blue water (NNBW). We also estimated ΔNNBW which is defined as an increase in NNBW from the past to the future. From the results, we could require the further development of water supply sources in order to sustain future water use. For coping with water scarcity using ΔNNBW, there is need for adaptation measure. To address adaptation measures, we need to set adaptation options which can be divided between 'Supply enhancement' and 'Demand management'. The supply enhancement includes increased storage, groundwater development, inter-basin transfer, desalination and re-use urban waste water. Demand management is defined as a set of actions controlling water demand by reducing water loss, increasing water productivity, and water re-allocation. In this study, we focus on estimating further future water demand under taking into account of several adaptation measures using H08 model.

An efficient unstructured WENO method for supersonic reactive flows

NASA Astrophysics Data System (ADS)

Zhao, Wen-Geng; Zheng, Hong-Wei; Liu, Feng-Jun; Shi, Xiao-Tian; Gao, Jun; Hu, Ning; Lv, Meng; Chen, Si-Cong; Zhao, Hong-Da

2018-03-01

An efficient high-order numerical method for supersonic reactive flows is proposed in this article. The reactive source term and convection term are solved separately by splitting scheme. In the reaction step, an adaptive time-step method is presented, which can improve the efficiency greatly. In the convection step, a third-order accurate weighted essentially non-oscillatory (WENO) method is adopted to reconstruct the solution in the unstructured grids. Numerical results show that our new method can capture the correct propagation speed of the detonation wave exactly even in coarse grids, while high order accuracy can be achieved in the smooth region. In addition, the proposed adaptive splitting method can reduce the computational cost greatly compared with the traditional splitting method.

High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter

PubMed Central

Xu, Dan; Zhou, Huan; Bai, Anning; Lu, Wei

2017-01-01

This paper presents an adaption of the fractional order terminal sliding mode control (AFTSMC) strategy for DC-DC Buck converter. The following strategy aims to design a novel nonlinear sliding surface function, with a double closed-loop structure of voltage and current. This strategy is a fusion of two characteristics: terminal sliding mode control (TSMC) and fractional order calculation (FOC). In addition, the influence of “the controller parameters” on the “performance of double closed-loop system” is investigated. It is observed that the value of terminal power has to be chosen to make a compromise between start-up and transient response of the converter. Therefore the AFTSMC strategy chooses the value of the terminal power adaptively, and this strategy can lead to the appropriate number of fractional order as well. Furthermore, through the fractional order analysis, the system can reach the sliding mode surface in a finite time. And the theoretical considerations are verified by numerical simulation. The performance of the AFTSMC and TSMC strategies is tested by computer simulations. And the comparison simulation results show that the AFTSMC exhibits a considerable improvement in terms of a faster output voltage response during load changes. Moreover, AFTSMC obtains a faster dynamical response, smaller steady-state error rate and lower overshoot. PMID:29084255

High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter.

PubMed

Wang, Jianlin; Xu, Dan; Zhou, Huan; Bai, Anning; Lu, Wei

2017-01-01

This paper presents an adaption of the fractional order terminal sliding mode control (AFTSMC) strategy for DC-DC Buck converter. The following strategy aims to design a novel nonlinear sliding surface function, with a double closed-loop structure of voltage and current. This strategy is a fusion of two characteristics: terminal sliding mode control (TSMC) and fractional order calculation (FOC). In addition, the influence of "the controller parameters" on the "performance of double closed-loop system" is investigated. It is observed that the value of terminal power has to be chosen to make a compromise between start-up and transient response of the converter. Therefore the AFTSMC strategy chooses the value of the terminal power adaptively, and this strategy can lead to the appropriate number of fractional order as well. Furthermore, through the fractional order analysis, the system can reach the sliding mode surface in a finite time. And the theoretical considerations are verified by numerical simulation. The performance of the AFTSMC and TSMC strategies is tested by computer simulations. And the comparison simulation results show that the AFTSMC exhibits a considerable improvement in terms of a faster output voltage response during load changes. Moreover, AFTSMC obtains a faster dynamical response, smaller steady-state error rate and lower overshoot.

L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

NASA Technical Reports Server (NTRS)

Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

2010-01-01

This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

Control of Initialized Fractional-Order Systems. Revised

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Control of Initialized Fractional-Order Systems

NASA Technical Reports Server (NTRS)

Hartly, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Model and experiments to optimize co-adaptation in a simplified myoelectric control system

NASA Astrophysics Data System (ADS)

Couraud, M.; Cattaert, D.; Paclet, F.; Oudeyer, P. Y.; de Rugy, A.

2018-04-01

Objective. To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. Approach. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. Results. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. Significance. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional myoelectric contexts are discussed.

Driver behaviour with adaptive cruise control.

PubMed

Stanton, Neville A; Young, Mark S

2005-08-15

This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1972-01-01

A survey was made of the literature devoted to the synthesis of model-tracking adaptive systems based on application of Liapunov's second method. The basic synthesis procedure is introduced and a critical review of extensions made to the theory since 1966 is made. The extensions relate to design for relative stability, reduction of order techniques, design with disturbance, design with time variable parameters, multivariable systems, identification, and an adaptive observer.

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

NASA Technical Reports Server (NTRS)

Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

2010-01-01

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Wavefront sensorless adaptive optics ophthalmoscopy in the human eye

PubMed Central

Hofer, Heidi; Sredar, Nripun; Queener, Hope; Li, Chaohong; Porter, Jason

2011-01-01

Wavefront sensor noise and fidelity place a fundamental limit on achievable image quality in current adaptive optics ophthalmoscopes. Additionally, the wavefront sensor ‘beacon’ can interfere with visual experiments. We demonstrate real-time (25 Hz), wavefront sensorless adaptive optics imaging in the living human eye with image quality rivaling that of wavefront sensor based control in the same system. A stochastic parallel gradient descent algorithm directly optimized the mean intensity in retinal image frames acquired with a confocal adaptive optics scanning laser ophthalmoscope (AOSLO). When imaging through natural, undilated pupils, both control methods resulted in comparable mean image intensities. However, when imaging through dilated pupils, image intensity was generally higher following wavefront sensor-based control. Despite the typically reduced intensity, image contrast was higher, on average, with sensorless control. Wavefront sensorless control is a viable option for imaging the living human eye and future refinements of this technique may result in even greater optical gains. PMID:21934779

Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

NASA Astrophysics Data System (ADS)

Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

2018-02-01

In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

Flexible manipulator control experiments and analysis

NASA Technical Reports Server (NTRS)

Yurkovich, S.; Ozguner, U.; Tzes, A.; Kotnik, P. T.

1987-01-01

Modeling and control design for flexible manipulators, both from an experimental and analytical viewpoint, are described. From the application perspective, an ongoing effort within the laboratory environment at the Ohio State University, where experimentation on a single link flexible arm is underway is described. Several unique features of this study are described here. First, the manipulator arm is slewed by a direct drive dc motor and has a rigid counterbalance appendage. Current experimentation is from two viewpoints: (1) rigid body slewing and vibration control via actuation with the hub motor, and (2) vibration suppression through the use of structure-mounted proof-mass actuation at the tip. Such an application to manipulator control is of interest particularly in design of space-based telerobotic control systems, but has received little attention to date. From an analytical viewpoint, parameter estimation techniques within the closed-loop for self-tuning adaptive control approaches are discussed. Also introduced is a control approach based on output feedback and frequency weighting to counteract effects of spillover in reduced-order model design. A model of the flexible manipulator based on experimental measurements is evaluated for such estimation and control approaches.

Adaptive control of dynamic balance in human gait on a split-belt treadmill.

PubMed

Buurke, Tom J W; Lamoth, Claudine J C; Vervoort, Danique; van der Woude, Lucas H V; den Otter, Rob

2018-05-17

Human bipedal gait is inherently unstable and staying upright requires adaptive control of dynamic balance. Little is known about adaptive control of dynamic balance in reaction to long-term, continuous perturbations. We examined how dynamic balance control adapts to a continuous perturbation in gait, by letting people walk faster with one leg than the other on a treadmill with two belts (i.e. split-belt walking). In addition, we assessed whether changes in mediolateral dynamic balance control coincide with changes in energy use during split-belt adaptation. In nine minutes of split-belt gait, mediolateral margins of stability and mediolateral foot roll-off changed during adaptation to the imposed gait asymmetry, especially on the fast side, and returned to baseline during washout. Interestingly, no changes in mediolateral foot placement (i.e. step width) were found during split-belt adaptation. Furthermore, the initial margin of stability and subsequent mediolateral foot roll-off were strongly coupled to maintain mediolateral dynamic balance throughout the gait cycle. Consistent with previous results net metabolic power was reduced during split-belt adaptation, but changes in mediolateral dynamic balance control were not correlated with the reduction of net metabolic power during split-belt adaptation. Overall, this study has shown that a complementary mechanism of relative foot positioning and mediolateral foot roll-off adapts to continuously imposed gait asymmetry to maintain dynamic balance in human bipedal gait. © 2018. Published by The Company of Biologists Ltd.

High-order adaptive secondary mirrors: where are we?

NASA Astrophysics Data System (ADS)

Salinari, Piero; Sandler, David G.

1998-09-01

We discuss the current developments and the perspective performances of adaptive secondary mirrors for high order adaptive a correction on large ground based telescopes. The development of the basic techniques involved a large collaborative effort of public research Institutes and of private companies is now essentially complete. The next crucial step will be the construction of an adaptive secondary mirror for the 6.5 m MMT. Problems such as the fabrication of very thin mirrors, the low cost implementation of fast position sensors, of efficient and compact electromagnetic actuators, of the control and communication electronics, of the actuator control system, of the thermal control and of the mechanical layout can be considered as solved, in some cases with more than one viable solution. To verify performances at system level two complete prototypes have been built and tested, one at ThermoTrex and the other at Arcetri. The two prototypes adopt the same basic approach concerning actuators, sensor and support of the thin mirror, but differ in a number of aspects such as the material of the rigid back plate used as reference for the thin mirror, the number and surface density of the actuators, the solution adopted for the removal of the heat, and the design of the electronics. We discuss how the results obtained by of the two prototypes and by numerical simulations will guide the design of full size adaptive secondary units.

Focused cognitive control in dishonesty: Evidence for predominantly transient conflict adaptation.

PubMed

Foerster, Anna; Pfister, Roland; Schmidts, Constantin; Dignath, David; Wirth, Robert; Kunde, Wilfried

2018-04-01

Giving a dishonest response to a question entails cognitive conflict due to an initial activation of the truthful response. Following conflict monitoring theory, dishonest responding could therefore elicit transient and sustained control adaptation processes to mitigate such conflict, and the current experiments take on the scope and specificity of such conflict adaptation in dishonesty. Transient adaptation reduces differences between honest and dishonest responding following a recent dishonest response. Sustained adaptation has a similar behavioral signature but is driven by the overall frequency of dishonest responding. Both types of adaptation to recent and frequent dishonest responses have been separately documented, leaving open whether control processes in dishonest responding can flexibly adapt to transient and sustained conflict signals of dishonest and other actions. This was the goal of the present experiments which studied (dis)honest responding to autobiographical yes/no questions. Experiment 1 showed robust transient adaptation to recent dishonest responses whereas sustained control adaptation failed to exert an influence on behavior. It further revealed that transient effects may create a spurious impression of sustained adaptation in typical experimental settings. Experiments 2 and 3 examined whether dishonest responding can profit from transient and sustained adaption processes triggered by other behavioral conflicts. This was clearly not the case: Dishonest responding adapted markedly to recent (dis)honest responses but not to any context of other conflicts. These findings indicate that control adaptation in dishonest responding is strong but surprisingly focused and they point to a potential trade-off between transient and sustained adaptation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Effect of vergence adaptation on convergence-accommodation: model simulations.

PubMed

Sreenivasan, Vidhyapriya; Bobier, William R; Irving, Elizabeth L; Lakshminarayanan, Vasudevan

2009-10-01

Several theoretical control models depict the adaptation effects observed in the accommodation and vergence mechanisms of the human visual system. Two current quantitative models differ in their approach of defining adaptation and in identifying the effect of controller adaptation on their respective cross-links between the vergence and accommodative systems. Here, we compare the simulation results of these adaptation models with empirical data obtained from emmetropic adults when they performed sustained near task through + 2D lens addition. The results of our experimental study showed an initial increase in exophoria (a divergent open-loop vergence position) and convergence-accommodation (CA) when viewing through +2D lenses. Prolonged fixation through the near addition lenses initiated vergence adaptation, which reduced the lens-induced exophoria and resulted in a concurrent reduction of CA. Both models showed good agreement with empirical measures of vergence adaptation. However, only one model predicted the experimental time course of reduction in CA. The pattern of our empirical results seem to be best described by the adaptation model that indicates the total vergence response to be a sum of two controllers, phasic and tonic, with the output of phasic controller providing input to the cross-link interactions.

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Domain-specific conflict adaptation without feature repetitions.

PubMed

Akçay, Çağlar; Hazeltine, Eliot

2011-06-01

An influential account of how cognitive control deals with conflicting sources of information holds that conflict is monitored by a module that automatically recruits attention to resolve the conflict. This leads to reduced effects of conflict on the subsequent trial, a phenomenon termed conflict adaptation. A prominent question is whether control processes are domain specific--that is, recruited only by the particular type of conflict they resolve. Previous studies that have examined this question used two-choice tasks in which feature repetition effects could be responsible for domain-specific adaptation effects. We report two experiments using four-choice (Experiment 1) and five-choice (Experiment 2) tasks that contain two types of irrelevant sources of potentially conflicting information: stimulus location (Simon conflict) and distractors (flanker conflict). In both experiments, we found within-type conflict adaptation for both types of conflict after eliminating trials on which stimulus features were repeated from one trial to the next. Across-type conflict adaptation, however, was not significant. Thus, conflict adaptation was due to domain-specific recruitment of cognitive control. Our results add converging evidence to the idea that multiple independent control processes are involved in reactive cognitive control, although whether control is always local remains to be determined.

Back-stepping active disturbance rejection control design for integrated missile guidance and control system via reduced-order ESO.

PubMed

Xingling, Shao; Honglun, Wang

2015-07-01

This paper proposes a novel composite integrated guidance and control (IGC) law for missile intercepting against unknown maneuvering target with multiple uncertainties and control constraint. First, by using back-stepping technique, the proposed IGC law design is separated into guidance loop and control loop. The unknown target maneuvers and variations of aerodynamics parameters in guidance and control loop are viewed as uncertainties, which are estimated and compensated by designed model-assisted reduced-order extended state observer (ESO). Second, based on the principle of active disturbance rejection control (ADRC), enhanced feedback linearization (FL) based control law is implemented for the IGC model using the estimates generated by reduced-order ESO. In addition, performance analysis and comparisons between ESO and reduced-order ESO are examined. Nonlinear tracking differentiator is employed to construct the derivative of virtual control command in the control loop. Third, the closed-loop stability for the considered system is established. Finally, the effectiveness of the proposed IGC law in enhanced interception performance such as smooth interception course, improved robustness against multiple uncertainties as well as reduced control consumption during initial phase are demonstrated through simulations. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

The PALM-3000 high-order adaptive optics system for Palomar Observatory

NASA Astrophysics Data System (ADS)

Bouchez, Antonin H.; Dekany, Richard G.; Angione, John R.; Baranec, Christoph; Britton, Matthew C.; Bui, Khanh; Burruss, Rick S.; Cromer, John L.; Guiwits, Stephen R.; Henning, John R.; Hickey, Jeff; McKenna, Daniel L.; Moore, Anna M.; Roberts, Jennifer E.; Trinh, Thang Q.; Troy, Mitchell; Truong, Tuan N.; Velur, Viswa

2008-07-01

Deployed as a multi-user shared facility on the 5.1 meter Hale Telescope at Palomar Observatory, the PALM-3000 highorder upgrade to the successful Palomar Adaptive Optics System will deliver extreme AO correction in the near-infrared, and diffraction-limited images down to visible wavelengths, using both natural and sodium laser guide stars. Wavefront control will be provided by two deformable mirrors, a 3368 active actuator woofer and 349 active actuator tweeter, controlled at up to 3 kHz using an innovative wavefront processor based on a cluster of 17 graphics processing units. A Shack-Hartmann wavefront sensor with selectable pupil sampling will provide high-order wavefront sensing, while an infrared tip/tilt sensor and visible truth wavefront sensor will provide low-order LGS control. Four back-end instruments are planned at first light: the PHARO near-infrared camera/spectrograph, the SWIFT visible light integral field spectrograph, Project 1640, a near-infrared coronagraphic integral field spectrograph, and 888Cam, a high-resolution visible light imager.

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

NASA Technical Reports Server (NTRS)

Al-Jiboory, Ali Khudhair; Zhu, Guoming; Swei, Sean Shan-Min; Su, Weihua; Nguyen, Nhan T.

2017-01-01

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

Multilevel adaptive control of nonlinear interconnected systems.

PubMed

Motallebzadeh, Farzaneh; Ozgoli, Sadjaad; Momeni, Hamid Reza

2015-01-01

This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Adapting improvements to context: when, why and how?

PubMed Central

Ovretveit, John; Dolan-Branton, Lisa; Marx, Michael; Reid, Amy; Reed, Julie; Agins, Bruce

2018-01-01

Abstract There is evidence that practitioners applying quality improvements often adapt the improvement method or the change they are implementing, either unknowingly, or intentionally to fit their service or situation. This has been observed especially in programs seeking to spread or ‘scale up’ an improvement change to other services. Sometimes their adaptations result in improved outcomes, sometimes they do not, and sometimes they do not have data make this assessment or to describe the adaptation. The purpose of this paper is to summarize key points about adaptation and context discussed at the Salzburg Global Seminar in order to help improvers judge when and how to adapt an improvement change. It aims also to encourage more research into such adaptations to develop our understanding of the when, why and how of effective adaptation and to provide more research informed guidance to improvers. The paper gives examples to illustrate key issues in adaptation and to consider more systematic and purposeful adaptation of improvements so as to increase the chances of achieving improvements in different settings for different participants. We describe methods for assessing whether adaptation is necessary or likely to reduce the effectiveness of an improvement intervention, which adaptations might be required, and methods for collecting data to assess whether the adaptations are successful. We also note areas where research is most needed in order to enable more effective scale up of quality improvements changes and wider take up and use of the methods.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition. PMID:28467371

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition.

The control of the controller: molecular mechanisms for robust perfect adaptation and temperature compensation.

PubMed

Ni, Xiao Yu; Drengstig, Tormod; Ruoff, Peter

2009-09-02

Organisms have the property to adapt to a changing environment and keep certain components within a cell regulated at the same level (homeostasis). "Perfect adaptation" describes an organism's response to an external stepwise perturbation by regulating some of its variables/components precisely to their original preperturbation values. Numerous examples of perfect adaptation/homeostasis have been found, as for example, in bacterial chemotaxis, photoreceptor responses, MAP kinase activities, or in metal-ion homeostasis. Two concepts have evolved to explain how perfect adaptation may be understood: In one approach (robust perfect adaptation), the adaptation is a network property, which is mostly, but not entirely, independent of rate constant values; in the other approach (nonrobust perfect adaptation), a fine-tuning of rate constant values is needed. Here we identify two classes of robust molecular homeostatic mechanisms, which compensate for environmental variations in a controlled variable's inflow or outflow fluxes, and allow for the presence of robust temperature compensation. These two classes of homeostatic mechanisms arise due to the fact that concentrations must have positive values. We show that the concept of integral control (or integral feedback), which leads to robust homeostasis, is associated with a control species that has to work under zero-order flux conditions and does not necessarily require the presence of a physico-chemical feedback structure. There are interesting links between the two identified classes of homeostatic mechanisms and molecular mechanisms found in mammalian iron and calcium homeostasis, indicating that homeostatic mechanisms may underlie similar molecular control structures.

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

NASA Technical Reports Server (NTRS)

Jacklin, Stephen; Schumann, Johann; Gupta, Pramod; Richard, Michael; Guenther, Kurt; Soares, Fola

2005-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Sensorimotor adaptation of speech in Parkinson's disease.

PubMed

Mollaei, Fatemeh; Shiller, Douglas M; Gracco, Vincent L

2013-10-01

The basal ganglia are involved in establishing motor plans for a wide range of behaviors. Parkinson's disease (PD) is a manifestation of basal ganglia dysfunction associated with a deficit in sensorimotor integration and difficulty in acquiring new motor sequences, thereby affecting motor learning. Previous studies of sensorimotor integration and sensorimotor adaptation in PD have focused on limb movements using visual and force-field alterations. Here, we report the results from a sensorimotor adaptation experiment investigating the ability of PD patients to make speech motor adjustments to a constant and predictable auditory feedback manipulation. Participants produced speech while their auditory feedback was altered and maintained in a manner consistent with a change in tongue position. The degree of adaptation was associated with the severity of motor symptoms. The patients with PD exhibited adaptation to the induced sensory error; however, the degree of adaptation was reduced compared with healthy, age-matched control participants. The reduced capacity to adapt to a change in auditory feedback is consistent with reduced gain in the sensorimotor system for speech and with previous studies demonstrating limitations in the adaptation of limb movements after changes in visual feedback among patients with PD. © 2013 Movement Disorder Society.

Cogging effect minimization in PMSM position servo system using dual high-order periodic adaptive learning compensation.

PubMed

Luo, Ying; Chen, Yangquan; Pi, Youguo

2010-10-01

Cogging effect which can be treated as a type of position-dependent periodic disturbance, is a serious disadvantage of the permanent magnetic synchronous motor (PMSM). In this paper, based on a simulation system model of PMSM position servo control, the cogging force, viscous friction, and applied load in the real PMSM control system are considered and presented. A dual high-order periodic adaptive learning compensation (DHO-PALC) method is proposed to minimize the cogging effect on the PMSM position and velocity servo system. In this DHO-PALC scheme, more than one previous periods stored information of both the composite tracking error and the estimate of the cogging force is used for the control law updating. Asymptotical stability proof with the proposed DHO-PALC scheme is presented. Simulation is implemented on the PMSM servo system model to illustrate the proposed method. When the constant speed reference is applied, the DHO-PALC can achieve a faster learning convergence speed than the first-order periodic adaptive learning compensation (FO-PALC). Moreover, when the designed reference signal changes periodically, the proposed DHO-PALC can obtain not only faster convergence speed, but also much smaller final error bound than the FO-PALC. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

PubMed

Fung, Wai-keung; Liu, Yun-hui

2003-12-01

Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

Solar adaptive optics with the DKIST: status report

NASA Astrophysics Data System (ADS)

Johnson, Luke C.; Cummings, Keith; Drobilek, Mark; Gregory, Scott; Hegwer, Steve; Johansson, Erik; Marino, Jose; Richards, Kit; Rimmele, Thomas; Sekulic, Predrag; Wöger, Friedrich

2014-08-01

The DKIST wavefront correction system will be an integral part of the telescope, providing active alignment control, wavefront correction, and jitter compensation to all DKIST instruments. The wavefront correction system will operate in four observing modes, diffraction-limited, seeing-limited on-disk, seeing-limited coronal, and limb occulting with image stabilization. Wavefront correction for DKIST includes two major components: active optics to correct low-order wavefront and alignment errors, and adaptive optics to correct wavefront errors and high-frequency jitter caused by atmospheric turbulence. The adaptive optics system is built around a fast tip-tilt mirror and a 1600 actuator deformable mirror, both of which are controlled by an FPGA-based real-time system running at 2 kHz. It is designed to achieve on-axis Strehl of 0.3 at 500 nm in median seeing (r0 = 7 cm) and Strehl of 0.6 at 630 nm in excellent seeing (r0 = 20 cm). We present the current status of the DKIST high-order adaptive optics, focusing on system design, hardware procurements, and error budget management.

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network based adaptive controller. While the fixed RBF network based controller which is tuned to compensate for control surface failures fails to achieve the same performance under modeling uncertainty and disturbances, the SORBFN is able to achieve good tracking convergence under all error conditions.

Glucocorticoid receptor haploinsufficiency causes hypertension and attenuates hypothalamic-pituitary-adrenal axis and blood pressure adaptions to high-fat diet

PubMed Central

Michailidou, Z.; Carter, R. N.; Marshall, E.; Sutherland, H. G.; Brownstein, D. G.; Owen, E.; Cockett, K.; Kelly, V.; Ramage, L.; Al-Dujaili, E. A. S.; Ross, M.; Maraki, I.; Newton, K.; Holmes, M. C.; Seckl, J. R.; Morton, N. M.; Kenyon, C. J.; Chapman, K. E.

2008-01-01

Glucocorticoid hormones are critical to respond and adapt to stress. Genetic variations in the glucocorticoid receptor (GR) gene alter hypothalamic-pituitary-adrenal (HPA) axis activity and associate with hypertension and susceptibility to metabolic disease. Here we test the hypothesis that reduced GR density alters blood pressure and glucose and lipid homeostasis and limits adaption to obesogenic diet. Heterozygous GRβgeo/+ mice were generated from embryonic stem (ES) cells with a gene trap integration of a β-galactosidase-neomycin phosphotransferase (βgeo) cassette into the GR gene creating a transcriptionally inactive GR fusion protein. Although GRβgeo/+ mice have 50% less functional GR, they have normal lipid and glucose homeostasis due to compensatory HPA axis activation but are hypertensive due to activation of the renin-angiotensin-aldosterone system (RAAS). When challenged with a high-fat diet, weight gain, adiposity, and glucose intolerance were similarly increased in control and GRβgeo/+ mice, suggesting preserved control of intermediary metabolism and energy balance. However, whereas a high-fat diet caused HPA activation and increased blood pressure in control mice, these adaptions were attenuated or abolished in GRβgeo/+ mice. Thus, reduced GR density balanced by HPA activation leaves glucocorticoid functions unaffected but mineralocorticoid functions increased, causing hypertension. Importantly, reduced GR limits HPA and blood pressure adaptions to obesogenic diet.—Michailidou, Z., Carter, R. N., Marshall, E., Sutherland, H. G., Brownstein, D. G., Owen, E., Cockett, K., Kelly, V., Ramage, L., Al-Dujaili, E. A. S., Ross, M., Maraki, I., Newton, K., Holmes, M. C., Seckl, J. R., Morton, N. M., Kenyon, C. J., Chapman, K. E. Glucocorticoid receptor haploinsufficiency causes hypertension and attenuates hypothalamic-pituitary-adrenal axis and blood pressure adaptions to high-fat diet. PMID:18697839

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Cardullo, Frank M.; Houck, Jacob A.

2002-01-01

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

Adaptive two-degree-of-freedom PI for speed control of permanent magnet synchronous motor based on fractional order GPC.

PubMed

Qiao, Wenjun; Tang, Xiaoqi; Zheng, Shiqi; Xie, Yuanlong; Song, Bao

2016-09-01

In this paper, an adaptive two-degree-of-freedom (2Dof) proportional-integral (PI) controller is proposed for the speed control of permanent magnet synchronous motor (PMSM). Firstly, an enhanced just-in-time learning technique consisting of two novel searching engines is presented to identify the model of the speed control system in a real-time manner. Secondly, a general formula is given to predict the future speed reference which is unavailable at the interval of two bus-communication cycles. Thirdly, the fractional order generalized predictive control (FOGPC) is introduced to improve the control performance of the servo drive system. Based on the identified model parameters and predicted speed reference, the optimal control law of FOGPC is derived. Finally, the designed 2Dof PI controller is auto-tuned by matching with the optimal control law. Simulations and real-time experimental results on the servo drive system of PMSM are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Laser diodes for sensing applications: adaptive cruise control and more

NASA Astrophysics Data System (ADS)

Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian

2005-02-01

Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.

An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size.

PubMed

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2014-09-01

Many papers have introduced adaptive clinical trial methods that allow modifications to the sample size based on interim estimates of treatment effect. There has been extensive commentary on type I error control and efficiency considerations, but little research on estimation after an adaptive hypothesis test. We evaluate the reliability and precision of different inferential procedures in the presence of an adaptive design with pre-specified rules for modifying the sampling plan. We extend group sequential orderings of the outcome space based on the stage at stopping, likelihood ratio statistic, and sample mean to the adaptive setting in order to compute median-unbiased point estimates, exact confidence intervals, and P-values uniformly distributed under the null hypothesis. The likelihood ratio ordering is found to average shorter confidence intervals and produce higher probabilities of P-values below important thresholds than alternative approaches. The bias adjusted mean demonstrates the lowest mean squared error among candidate point estimates. A conditional error-based approach in the literature has the benefit of being the only method that accommodates unplanned adaptations. We compare the performance of this and other methods in order to quantify the cost of failing to plan ahead in settings where adaptations could realistically be pre-specified at the design stage. We find the cost to be meaningful for all designs and treatment effects considered, and to be substantial for designs frequently proposed in the literature. © 2014, The International Biometric Society.

Adaptive Offset Correction for Intracortical Brain Computer Interfaces

PubMed Central

Homer, Mark L.; Perge, János A.; Black, Michael J.; Harrison, Matthew T.; Cash, Sydney S.; Hochberg, Leigh R.

2014-01-01

Intracortical brain computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user’s ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called MOCA, was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ±10.1%; p<0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs. PMID:24196868

Adaptive offset correction for intracortical brain-computer interfaces.

PubMed

Homer, Mark L; Perge, Janos A; Black, Michael J; Harrison, Matthew T; Cash, Sydney S; Hochberg, Leigh R

2014-03-01

Intracortical brain-computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user's ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called multiple offset correction algorithm (MOCA), was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors ( 10.6 ± 10.1% ; p < 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.

Incidence of whooping cough in Spain (1997-2010): an underreported disease.

PubMed

Fernández-Cano, María Isabel; Armadans Gil, Lluís; Martínez Gómez, Xavi; Campins Martí, Magda

2014-06-01

Whooping cough is currently the worst controlled vaccine-preventable disease in the majority of countries. In order to reduce its morbidity and mortality, it is essential to adapt vaccination programmes to data provided by epidemiological surveillance. A population-based retrospective epidemiological study to estimate the minimum annual undernotification rate of pertussis in Spain from 1997 to 2010 was performed. The incidence of pertussis cases reported to the National Notifiable Disease Surveillance System was compared with the incidence of hospital discharges for pertussis from the National Surveillance System for hospital data, Conjunto Mínimo Básico de Datos. The overall reported incidence and that of hospitalisation for whooping cough were 1.3 cases × 100,000 inhabitants in both cases. Minimum underreporting oscillated between 3.8 and 22.8 %, according to the year of the study. The greatest underreporting (50 %) was observed in children under the age of 1 year. Spanish epidemiological surveillance system of pertussis should be improved with complementary active systems to ascertain the real incidence. Paediatricians and general practitioners should be sensibilized to the importance of notification because this would be essential for adapting the prevention and control measures of this disease.

Effect of spaceflight on isoflavonoid accumulation in etiolated soybean seedlings

NASA Technical Reports Server (NTRS)

Levine, L. H.; Levine, H. G.; Stryjewski, E. C.; Prima, V.; Piastuch, W. C.; Sager, J. S. (Principal Investigator)

2001-01-01

In order to explore the potential impact of microgravity on flavonoid biosynthesis, we examined isoflavonoid levels in soybean (Glycine max) tissues generated under both spaceflight and clinorotation conditions. A 6-day Space Shuttle-based microgravity exposure resulted in enhanced accumulation of isoflavone glycosides (daidzin, 6"-O-malonyl-7-O-glucosyl daidzein, genistin, 6"-O-malonyl-7-O-glucosyl genistein) in hypocotyl and root tissues, but reduced levels in cotyledons (relative to 1g controls on Earth). Soybean seedlings grown on a horizontally rotating clinostat for 3, 4 and 5 days exhibited (relative to a vertical clinorotation control) an isoflavonoid accumulation pattern similar to the space-grown tissues. Elevated isoflavonoid levels attributable to the clinorotation treatment were transient, with the greatest increase observed in the three-day-treated tissues and smaller increases in the four- and five-day-treated tissues. Differences between stresses presented by spaceflight and clinorotation and the resulting biochemical adaptations are discussed, as is whether the increase in isoflavonoid concentrations were due to differential rates of development under the "gravity" treatments employed. Results suggest that spaceflight exposure does not impair isoflavonoid accumulation in developing soybean tissues and that isoflavonoids respond positively to microgravity as a biochemical strategy of adaptation.

Automation of temperature control for large-array microwave surface applicators.

PubMed

Zhou, L; Fessenden, P

1993-01-01

An adaptive temperature control system has been developed for the microstrip antenna array applicators used for large area superficial hyperthermia. A recursive algorithm which allows rapid power updating even for large antenna arrays and accounts for coupling between neighbouring antennas has been developed, based on a first-order difference equation model. Surface temperatures from the centre of each antenna element are the primary feedback information. Also used are temperatures from additional surface probes placed within the treatment field to protect locations vulnerable to excessive temperatures. In addition, temperatures at depth are observed by mappers and utilized to restrain power to reduce treatment-related complications. Experiments on a tissue-equivalent phantom capable of dynamic differential cooling have successfully verified this temperature control system. The results with the 25 (5 x 5) antenna array have demonstrated that during dynamic water cooling changes and other experimentally simulated disturbances, the controlled temperatures converge to desired temperature patterns with a precision close to the resolution of the thermometry system (0.1 degree C).

Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Krishnamoorthy, Kiruthika

Trajectory tracking is a critical element for the better functionality of autonomous vehicles. The main objective of this research study was to implement and analyze L1 adaptive control laws for autonomous flight under normal and upset flight conditions. The West Virginia University (WVU) Unmanned Aerial Vehicle flight simulation environment was used for this purpose. A comparison study between the L1 adaptive controller and a baseline conventional controller, which relies on position, proportional, and integral compensation, has been performed for a reduced size jet aircraft, the WVU YF-22. Special attention was given to the performance of the proposed control laws in the presence of abnormal conditions. The abnormal conditions considered are locked actuators (stabilator, aileron, and rudder) and excessive turbulence. Several levels of abnormal condition severity have been considered. The performance of the control laws was assessed over different-shape commanded trajectories. A set of comprehensive evaluation metrics was defined and used to analyze the performance of autonomous flight control laws in terms of control activity and trajectory tracking errors. The developed L1 adaptive control laws are supported by theoretical stability guarantees. The simulation results show that L1 adaptive output feedback controller achieves better trajectory tracking with lower level of control actuation as compared to the baseline linear controller under nominal and abnormal conditions.

A Randomized Controlled Pilot Trial of Different Mobile Messaging Interventions for Problem Drinking Compared to Weekly Drink Tracking

PubMed Central

van Stolk-Cooke, Katherine; Kuerbis, Alexis; Stadler, Gertraud; Baumel, Amit; Shao, Sijing; McKay, James R.; Morgenstern, Jon

2017-01-01

Introduction Recent evidence suggests that text messaging may help to reduce problem drinking as an extension to in-person services, but very little is known about the effectiveness of remote messaging on problem drinking as a stand-alone intervention, or how different types of messages may improve drinking outcomes in those seeking to moderate their alcohol consumption. Methods We conducted an exploratory, single-blind randomized controlled pilot study comparing four different types of alcohol reduction-themed text messages sent daily to weekly drink self-tracking texts in order to determine their impact on drinking outcomes over a 12-week period in 152 participants (≈ 30 per group) seeking to reduce their drinking on the internet. Messaging interventions included: weekly drink self-tracking mobile assessment texts (MA), loss-framed texts (LF), gain-framed texts (GF), static tailored texts (ST), and adaptive tailored texts (TA). Poisson and least squares regressions were used to compare differences between each active messaging group and the MA control. Results When adjusting for baseline drinking, participants in all messaging groups except GF significantly reduced the number of drinks consumed per week and the number of heavy drinking days compared to MA. Only the TA and GF groups were significantly different from MA in reducing the number of drinking days. While the TA group yielded the largest effect sizes on all outcome measures, there were no significant differences between active messaging groups on any outcome measure. 79.6% of individuals enrolled in the study wanted to continue receiving messages for an additional 12 weeks at the end of the study. Discussion Results of this pilot study indicate that remote automated text messages delivered daily can help adult problem drinkers reduce drinking frequency and quantity significantly more than once-a-week self-tracking messages only, and that tailored adaptive texts yield the largest effect sizes across outcomes compared to MA. Larger samples are needed to understand differences between messaging interventions and to target their mechanisms of efficacy. PMID:28146560

High-Fidelity Geometric Modeling and Mesh Generation for Mechanics Characterization of Polycrystalline Materials

DTIC Science & Technology

2014-10-26

From the parameterization results, we extract adaptive and anisotropic T-meshes for the further T- spline surface construction. Finally, a gradient flow...field-based method [7, 12] to generate adaptive and anisotropic quadrilateral meshes, which can be used as the control mesh for high-order T- spline ...parameterization results, we extract adaptive and anisotropic T-meshes for the further T- spline surface construction. Finally, a gradient flow-based

The synchronisation of fractional-order hyperchaos compound system

NASA Astrophysics Data System (ADS)

Noghredani, Naeimadeen; Riahi, Aminreza; Pariz, Naser; Karimpour, Ali

2018-02-01

This paper presents a new compound synchronisation scheme among four hyperchaotic memristor system with incommensurate fractional-order derivatives. First a new controller was designed based on adaptive technique to minimise the errors and guarantee compound synchronisation of four fractional-order memristor chaotic systems. According to the suitability of compound synchronisation as a reliable solution for secure communication, we then examined the application of the proposed adaptive compound synchronisation scheme in the presence of noise for secure communication. In addition, the unpredictability and complexity of the drive systems enhance the security of secure communication. The corresponding theoretical analysis and results of simulation validated the effectiveness of the proposed synchronisation scheme using MATLAB.

A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks.

PubMed

Xiong, Hailiang; Zhang, Wensheng; Xu, Hongji; Du, Zhengfeng; Tang, Huaibin; Li, Jing

2017-05-25

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems.

A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks

PubMed Central

Xiong, Hailiang; Zhang, Wensheng; Xu, Hongji; Du, Zhengfeng; Tang, Huaibin; Li, Jing

2017-01-01

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems. PMID:28587085

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.

PubMed

Sarhadi, Pouria; Noei, Abolfazl Ranjbar; Khosravi, Alireza

2016-11-01

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Deal or no deal: can incentives encourage widespread adoption of intelligent speed adaptation devices?

PubMed

Chorlton, Kathryn; Hess, Stephane; Jamson, Samantha; Wardman, Mark

2012-09-01

Given the burden of injury, economic, environmental and social consequences associated with speeding, reducing road traffic speed remains a major priority. Intelligent speed adaptation (ISA) is a promising but controversial new in-vehicle system that provides drivers with support on the speed-control task. In order to model potential system uptake, this paper explores drivers' preferences for two different types of ISA given a number of alternative fiscal incentives and non-fiscal measures, using a stated preference approach. As would be expected with such a contentious issue, the analysis revealed the presence of significant variations in sensitivities and preferences in the sample. While a non-negligible part of the sample population has such strong opposition to ISA that no reasonable discounts or incentives would lead to them buying or accepting such a system, there is also a large part of the population that, if given the right incentives, would be willing or even keen to equip their vehicle with an ISA device. Copyright © 2011. Published by Elsevier Ltd.

Implementation and on-sky results of an optimal wavefront controller for the MMT NGS adaptive optics system

NASA Astrophysics Data System (ADS)

Powell, Keith B.; Vaitheeswaran, Vidhya

2010-07-01

The MMT observatory has recently implemented and tested an optimal wavefront controller for the NGS adaptive optics system. Open loop atmospheric data collected at the telescope is used as the input to a MATLAB based analytical model. The model uses nonlinear constrained minimization to determine controller gains and optimize the system performance. The real-time controller performing the adaptive optics close loop operation is implemented on a dedicated high performance PC based quad core server. The controller algorithm is written in C and uses the GNU scientific library for linear algebra. Tests at the MMT confirmed the optimal controller significantly reduced the residual RMS wavefront compared with the previous controller. Significant reductions in image FWHM and increased peak intensities were obtained in J, H and K-bands. The optimal PID controller is now operating as the baseline wavefront controller for the MMT NGS-AO system.

Evaluation of instrumentation systems in reducing E. faecalis from root canals: TF adaptive and ProTaper next versus single file systems.

PubMed

Karataş, Ertuğrul; Gültekin, Esra; Arslan, Hakan; Kirici, Damla Özsu; Alsancak, Meltem; Topçu, Meltem Çolak

2015-03-01

To compare the effect of the TF Adaptive, ProTaper Next, OneShape, WaveOne, Reciproc, (SAF) on the reduction of E. faecalis in experimentally infected root canals. 70 human mandibular incisor teeth with straight roots and single root canals were selected for this experiment and the root canals of the selected teeth were infected with E. faecalis. After contamination, all the root canals were randomly divided into 7 groups: control, ProTaper Next, TF Adaptive, SAF, WaveOne, Reciproc, and OneShape. After the irrigation procedures, samples were taken from root canals with paper points and incubated in blood agar plates. The colonies grown on the blood agar were counted and interpreted as colony forming units per milliliter. Analysis of results showed that all instrumentation systems were more effective in reducing the number of bacteria than the control (P<.001). The ProTaper Next, TF Adaptive, WaveOne, Reciproc, and OneShape systems were significantly more effective than the SAF system in reducing E. faecalis within the root canals (P<.001). All instrumentation systems used in this study provided a significant reduction in bacterial populations.

Accounting for sequential trial effects in the flanker task: conflict adaptation or associative priming?

PubMed

Nieuwenhuis, Sander; Stins, John F; Posthuma, Danielle; Polderman, Tinca J C; Boomsma, Dorret I; de Geus, Eco J

2006-09-01

The conflict-control loop theory proposes that the detection of conflict in information processing triggers an increase in cognitive control, resulting in improved performance on the subsequent trial. This theory seems consistent with the robust finding that conflict susceptibility is reduced following correct trials associated with high conflict: the conflict adaptation effect. However, despite providing favorable conditions for eliciting and detecting conflict-triggered performance adjustments, none of the five experiments reported here provide unequivocal evidence of such adjustments. Instead, the results corroborate and extend earlier findings by demonstrating that the conflict adaptation effect, at least in the flanker task, is only present for a specific subset of trial sequences that is characterized by a response repetition. This pattern of results provides strong evidence that the conflict adaptation effect reflects associative stimulus-response priming instead of conflict-driven adaptations in cognitive control.

Direct Adaptive Rejection of Vortex-Induced Disturbances for a Powered SPAR Platform

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Balas, Mark J.; VanZwieten, James H.; Driscoll, Frederick R.

2009-01-01

The Rapidly Deployable Stable Platform (RDSP) is a novel vessel designed to be a reconfigurable, stable at-sea platform. It consists of a detachable catamaran and spar, performing missions with the spar extending vertically below the catamaran and hoisting it completely out of the water. Multiple thrusters located along the spar allow it to be actively controlled in this configuration. A controller is presented in this work that uses an adaptive feedback algorithm in conjunction with Direct Adaptive Disturbance Rejection (DADR) to mitigate persistent, vortex-induced disturbances. Given the frequency of a disturbance, the nominal DADR scheme adaptively compensates for its unknown amplitude and phase. This algorithm is extended to adapt to a disturbance frequency that is only coarsely known by including a Phase Locked Loop (PLL). The PLL improves the frequency estimate on-line, allowing the modified controller to reduce vortex-induced motions by more than 95% using achievable thrust inputs.

Development of a Voice Activity Controlled Noise Canceller

PubMed Central

Abid Noor, Ali O.; Samad, Salina Abdul; Hussain, Aini

2012-01-01

In this paper, a variable threshold voice activity detector (VAD) is developed to control the operation of a two-sensor adaptive noise canceller (ANC). The VAD prohibits the reference input of the ANC from containing some strength of actual speech signal during adaptation periods. The novelty of this approach resides in using the residual output from the noise canceller to control the decisions made by the VAD. Thresholds of full-band energy and zero-crossing features are adjusted according to the residual output of the adaptive filter. Performance evaluation of the proposed approach is quoted in terms of signal to noise ratio improvements as well mean square error (MSE) convergence of the ANC. The new approach showed an improved noise cancellation performance when tested under several types of environmental noise. Furthermore, the computational power of the adaptive process is reduced since the output of the adaptive filter is efficiently calculated only during non-speech periods. PMID:22778667

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows.

PubMed

Kirkeby, Carsten; Græsbøll, Kaare; Nielsen, Søren Saxmose; Christiansen, Lasse Engbo; Toft, Nils; Halasa, Tariq

2016-01-01

Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP) in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.

Adaptive control of servo system based on LuGre model

NASA Astrophysics Data System (ADS)

Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

2018-03-01

This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Modeling Fire Emissions across Central and Southern Italy: Implications for Land and Fire Management

NASA Astrophysics Data System (ADS)

Bacciu, V. M.; Salis, M.; Spano, D.

2015-12-01

Fires play a relevant role in the global and regional carbon cycle, representing a remarkable source of CO2 and other greenhouse gases (GHG) that influence atmosphere budgets and climate. In addition, the wildfire increase projected in Southern Europe due to climate change (CC) and concurrent exacerbation of extreme weather conditions could also lead to a significant rise in GHG. Recently, in the context of the Italian National Adaptation Strategy to Climate Change (SNAC), several approaches were identified as valuable tools to adapt and mitigate the impacts of CC on wildfires, in order to reduce landscape susceptibility and to contribute to the efforts of carbon emission mitigation proposed within the Kyoto protocol. Active forest and fuel management (such as prescribed burning, fuel reduction and removal, weed and flammable shrub control, creation of fuel discontinuity) is recognised to be a key element to adapt and mitigate the impacts of CC on wildfires. Despite this, overall there is a lack of studies about the effectiveness of fire emission mitigation strategies. The current work aims to analyse the potential of a combination of fuel management practices in mitigating emissions from forest fires and evaluate valuable and viable options across Central and Southern Italy. These objectives were achieved throughout a retrospective application of an integrated approach combining a fire emission model (FOFEM - First Order Fire Effect Model) with spatially explicit, comprehensive, and accurate fire, vegetation and weather data for the period 2004-2012. Furthermore, a number of silvicultural techniques were combined to develop several fuel management scenarios and then tested to evaluate their potential in mitigating fire emissions.The preliminary results showed the crucial role of appropriate fuel, fire behavior, and weather data to reduce bias in quantifying the source and the composition of fire emissions and to attain reasonable estimations. Also, the current study highlighted that balanced combination of fuel management techniques could not only be a viable mean to reduce fire emissions but at the same time prevent future wildfires and the related threat to human lives and activities.

Adaptation to changes in higher-order stimulus statistics in the salamander retina.

PubMed

Tkačik, Gašper; Ghosh, Anandamohan; Schneidman, Elad; Segev, Ronen

2014-01-01

Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices

NASA Astrophysics Data System (ADS)

Chen, Xi; Li, Yancheng; Li, Jianchun; Gu, Xiaoyu

2018-01-01

Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov’s direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.

Nonlinear adaptive formation control for a class of autonomous holonomic planetary exploration rovers

NASA Astrophysics Data System (ADS)

Ganji, Farid

This dissertation presents novel nonlinear adaptive formation controllers for a heterogeneous group of holonomic planetary exploration rovers navigating over flat terrains with unknown soil types and surface conditions. A leader-follower formation control architecture is employed. In the first part, using a point-mass model for robots and a Coulomb-viscous friction model for terrain resistance, direct adaptive control laws and a formation speed-adaptation strategy are developed for formation navigation over unknown and changing terrain in the presence of actuator saturation. On-line estimates of terrain frictional parameters compensate for unknown terrain resistance and its variations. In saturation events over difficult terrain, the formation speed is reduced based on the speed of the slowest saturated robot, using internal fleet communication and a speed-adaptation strategy, so that the formation error stays bounded and small. A formal proof for asymptotic stability of the formation system in non-saturated conditions is given. The performance of robot controllers are verified using a modular 3-robot formation simulator. Simulations show that the formation errors reduce to zero asymptotically under non-saturated conditions as is guaranteed by the theoretical proof. In the second part, the proposed adaptive control methodology is extended for formation control of a class of omnidirectional rovers with three independently-driven universal holonomic rigid wheels, where the rovers' rigid-body dynamics, drive-system electromechanical characteristics, and wheel-ground interaction mechanics are incorporated. Holonomic rovers have the ability to move simultaneously and independently in translation and rotation, rendering great maneuverability and agility, which makes them suitable for formation navigation. Novel nonlinear adaptive control laws are designed for the input voltages of the three wheel-drive motors. The motion resistance, which is due to the sinkage of rover wheels in soft planetary terrain, is modeled using classical terramechanics theory. The unknown system parameters for adaptive estimation pertain to the rolling resistance forces and scrubbing resistance torques at the wheel-terrain interfaces. Novel terramechanical formulas for terrain resistance forces and torques are derived via considering the universal holonomic wheels as rigid toroidal wheels moving forward and/or sideways as well as turning on soft ground. The asymptotic stability of the formation control system is rigorously proved using Lyapunov's direct method.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

NASA Astrophysics Data System (ADS)

Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

2018-03-01

In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

Sex-biased hatching order and adaptive population divergence in a passerine bird.

PubMed

Badyaev, Alexander V; Hill, Geoffrey E; Beck, Michelle L; Dervan, Anne A; Duckworth, Renee A; McGraw, Kevin J; Nolan, Paul M; Whittingham, Linda A

2002-01-11

Most species of birds can lay only one egg per day until a clutch is complete, and the order in which eggs are laid often has strong and sex-specific effects on offspring growth and survival. In two recently established populations of the house finch (Carpodacus mexicanus) in Montana and Alabama, breeding females simultaneously adjusted the sex and growth of offspring in relation to their position in the laying order, thereby reducing the mortality of sons and daughters by 10 to 20% in both environments. We show experimentally that the reduction in mortality is produced by persistent and sex-specific maternal effects on the growth and morphology of offspring. These strong parental effects may have facilitated the rapid adaptive divergence among populations of house finches.

Anisotropic mesh adaptation for marine ice-sheet modelling

NASA Astrophysics Data System (ADS)

Gillet-Chaulet, Fabien; Tavard, Laure; Merino, Nacho; Peyaud, Vincent; Brondex, Julien; Durand, Gael; Gagliardini, Olivier

2017-04-01

Improving forecasts of ice-sheets contribution to sea-level rise requires, amongst others, to correctly model the dynamics of the grounding line (GL), i.e. the line where the ice detaches from its underlying bed and goes afloat on the ocean. Many numerical studies, including the intercomparison exercises MISMIP and MISMIP3D, have shown that grid refinement in the GL vicinity is a key component to obtain reliable results. Improving model accuracy while maintaining the computational cost affordable has then been an important target for the development of marine icesheet models. Adaptive mesh refinement (AMR) is a method where the accuracy of the solution is controlled by spatially adapting the mesh size. It has become popular in models using the finite element method as they naturally deal with unstructured meshes, but block-structured AMR has also been successfully applied to model GL dynamics. The main difficulty with AMR is to find efficient and reliable estimators of the numerical error to control the mesh size. Here, we use the estimator proposed by Frey and Alauzet (2015). Based on the interpolation error, it has been found effective in practice to control the numerical error, and has some flexibility, such as its ability to combine metrics for different variables, that makes it attractive. Routines to compute the anisotropic metric defining the mesh size have been implemented in the finite element ice flow model Elmer/Ice (Gagliardini et al., 2013). The mesh adaptation is performed using the freely available library MMG (Dapogny et al., 2014) called from Elmer/Ice. Using a setup based on the inter-comparison exercise MISMIP+ (Asay-Davis et al., 2016), we study the accuracy of the solution when the mesh is adapted using various variables (ice thickness, velocity, basal drag, …). We show that combining these variables allows to reduce the number of mesh nodes by more than one order of magnitude, for the same numerical accuracy, when compared to uniform mesh refinement. For transient solutions where the GL is moving, we have implemented an algorithm where the computation is reiterated allowing to anticipate the GL displacement and to adapt the mesh to the transient solution. We discuss the performance and robustness of this algorithm.

O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

PubMed

Chen, Jiejie; Chen, Boshan; Zeng, Zhigang

2018-04-01

This paper investigates O(t -α )-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and differential inclusion theory, using a Razumikhin-type method, some sufficient conditions ensuring the global O(t -α )-synchronization of considered networks are established via a linear-type discontinuous control. Next, a new fractional differential inequality is established and two new discontinuous adaptive controller is designed to achieve Mittag-Leffler synchronization between the drive system and the response systems using this inequality. Finally, two numerical simulations are given to show the effectiveness of the theoretical results. Our approach and theoretical results have a leading significance in the design of synchronized fractional-order memristive neural networks circuits involving discontinuous activations and time-varying delays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Determinants of climate change adaptation strategies used by fish farmers in Epe Local Government Area of Lagos State, Nigeria.

PubMed

Arimi, Kayode S

2014-05-01

Undesirable impacts of climate change have been a common occurrence that has made fish farmers in developing countries adopt some climate-change adaptation strategies. However, little is known about determinants of climate-change adaptation strategies used by these fish farmers. This study, therefore, articulates novelties on adaptation to climate change, as well ascertains determinants of adaptation strategies used by fish farmers in Epe, Lagos State, Nigeria. Climate change adaptation strategies mostly used by fish farmers include frequent seeking for early warning information about climate change (76.7%) and avoidance of areas susceptible to flooding (60.0%). Climate-change adaptation strategies used by fish farmers were significantly influenced by access to early warning information (β = 7.21), knowledge of farmers about climate change adaptation strategies (β = 8.86), access to capital (β = 28.25), and participation in workshop and conferences (β = 37.19) but were reduced by number of fish stocking (β = -2.06). The adaptation strategies used by fish farmers were autonomous and mostly determined by the access to credit facilities and information. Development policy should focus on carbon capture and storage technology in order to reduce adverse impacts of climate change, as well as making early warning information on climate change available to fish farmers. These will enhance adaptation to climate change. © 2013 Society of Chemical Industry.

Adaptive nonsingular fast terminal sliding-mode control for the tracking problem of uncertain dynamical systems.

PubMed

Boukattaya, Mohamed; Mezghani, Neila; Damak, Tarak

2018-06-01

In this paper, robust and adaptive nonsingular fast terminal sliding-mode (NFTSM) control schemes for the trajectory tracking problem are proposed with known or unknown upper bound of the system uncertainty and external disturbances. The developed controllers take the advantage of the NFTSM theory to ensure fast convergence rate, singularity avoidance, and robustness against uncertainties and external disturbances. First, a robust NFTSM controller is proposed which guarantees that sliding surface and equilibrium point can be reached in a short finite-time from any initial state. Then, in order to cope with the unknown upper bound of the system uncertainty which may be occurring in practical applications, a new adaptive NFTSM algorithm is developed. One feature of the proposed control law is their adaptation techniques where the prior knowledge of parameters uncertainty and disturbances is not needed. However, the adaptive tuning law can estimate the upper bound of these uncertainties using only position and velocity measurements. Moreover, the proposed controller eliminates the chattering effect without losing the robustness property and the precision. Stability analysis is performed using the Lyapunov stability theory, and simulation studies are conducted to verify the effectiveness of the developed control schemes. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Automation of a portable extracorporeal circulatory support system with adaptive fuzzy controllers.

PubMed

Mendoza García, A; Krane, M; Baumgartner, B; Sprunk, N; Schreiber, U; Eichhorn, S; Lange, R; Knoll, A

2014-08-01

The presented work relates to the procedure followed for the automation of a portable extracorporeal circulatory support system. Such a device may help increase the chances of survival after suffering from cardiogenic shock outside the hospital, additionally a controller can provide of optimal organ perfusion, while reducing the workload of the operator. Animal experiments were carried out for the acquisition of haemodynamic behaviour of the body under extracorporeal circulation. A mathematical model was constructed based on the experimental data, including a cardiovascular model, gas exchange and the administration of medication. As the base of the controller fuzzy logic was used allowing the easy integration of knowledge from trained perfusionists, an adaptive mechanism was included to adapt to the patient's individual response. Initial simulations show the effectiveness of the controller and the improvements of perfusion after adaptation. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Adaptive parametric model order reduction technique for optimization of vibro-acoustic models: Application to hearing aid design

NASA Astrophysics Data System (ADS)

Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin

2018-06-01

Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.

Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller.

PubMed

Lin, Chih-Min; Yang, Ming-Shu; Chao, Fei; Hu, Xiao-Min; Zhang, Jun

2016-10-01

This paper aims to propose an efficient network and applies it as an adaptive filter for the signal processing problems. An adaptive filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so that the convergence of the filtering error can be guaranteed. In order to demonstrate the performance of the proposed adaptive T2FCMAC filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an adaptive noise cancellation system. The advantages of the proposed filter over the other adaptive filters are verified through simulations.

Analysis, preliminary design and simulation systems for control-structure interaction problems

NASA Technical Reports Server (NTRS)

Park, K. C.; Alvin, Kenneth F.

1991-01-01

Software aspects of control-structure interaction (CSI) analysis are discussed. The following subject areas are covered: (1) implementation of a partitioned algorithm for simulation of large CSI problems; (2) second-order discrete Kalman filtering equations for CSI simulations; and (3) parallel computations and control of adaptive structures.

Handwritten word preprocessing for database adaptation

NASA Astrophysics Data System (ADS)

Oprean, Cristina; Likforman-Sulem, Laurence; Mokbel, Chafic

2013-01-01

Handwriting recognition systems are typically trained using publicly available databases, where data have been collected in controlled conditions (image resolution, paper background, noise level,...). Since this is not often the case in real-world scenarios, classification performance can be affected when novel data is presented to the word recognition system. To overcome this problem, we present in this paper a new approach called database adaptation. It consists of processing one set (training or test) in order to adapt it to the other set (test or training, respectively). Specifically, two kinds of preprocessing, namely stroke thickness normalization and pixel intensity normalization are considered. The advantage of such approach is that we can re-use the existing recognition system trained on controlled data. We conduct several experiments with the Rimes 2011 word database and with a real-world database. We adapt either the test set or the training set. Results show that training set adaptation achieves better results than test set adaptation, at the cost of a second training stage on the adapted data. Accuracy of data set adaptation is increased by 2% to 3% in absolute value over no adaptation.

Autonomous watersheds: Reducing flooding and stream erosion through real-time control

NASA Astrophysics Data System (ADS)

Kerkez, B.; Wong, B. P.

2017-12-01

We introduce an analytical toolchain, based on dynamical system theory and feedback control, to determine how many control points (valves, gates, pumps, etc.) are needed to transform urban watersheds from static to adaptive. Advances and distributed sensing and control stand to fundamentally change how we manage urban watersheds. In lieu of new and costly infrastructure, the real-time control of stormwater systems will reduce flooding, mitigate stream erosion, and improve the treatment of polluted runoff. We discuss the how open source technologies, in the form of wireless sensor nodes and remotely-controllable valves (open-storm.org), have been deployed to build "smart" stormwater systems in the Midwestern US. Unlike "static" infrastructure, which cannot readily adapt to changing inputs and land uses, these distributed control assets allow entire watersheds to be reconfigured on a storm-by-storm basis. Our results show how the control of even just a few valves within urban catchments (1-10km^2) allows for the real-time "shaping" of hydrographs, which reduces downstream erosion and flooding. We also introduce an equivalence framework that can be used by decision-makers to objectively compare investments into "smart" system to more traditional solutions, such as gray and green stormwater infrastructure.

Neural Flight Control System

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen

2003-01-01

The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

Neural network-based model reference adaptive control system.

PubMed

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

Adaptive beam shaping by controlled thermal lensing in optical elements

NASA Astrophysics Data System (ADS)

Arain, Muzammil A.; Quetschke, Volker; Gleason, Joseph; Williams, Luke F.; Rakhmanov, Malik; Lee, Jinho; Cruz, Rachel J.; Mueller, Guido; Tanner, D. B.; Reitze, David. H.

2007-04-01

We describe an adaptive optical system for use as a tunable focusing element. The system provides adaptive beam shaping via controlled thermal lensing in the optical elements. The system is agile, remotely controllable, touch free, and vacuum compatible; it offers a wide dynamic range, aberration-free focal length tuning, and can provide both positive and negative lensing effects. Focusing is obtained through dynamic heating of an optical element by an external pump beam. The system is especially suitable for use in interferometric gravitational wave interferometers employing high laser power, allowing for in situ control of the laser modal properties and compensation for thermal lensing of the primary laser. Using CO2 laser heating of fused-silica substrates, we demonstrate a focal length variable from infinity to 4.0 m, with a slope of 0.082 diopter/W of absorbed heat. For on-axis operation, no higher-order modes are introduced by the adaptive optical element. Theoretical modeling of the induced optical path change and predicted thermal lens agrees well with measurement.

Adaptive beam shaping by controlled thermal lensing in optical elements.

PubMed

Arain, Muzammil A; Quetschke, Volker; Gleason, Joseph; Williams, Luke F; Rakhmanov, Malik; Lee, Jinho; Cruz, Rachel J; Mueller, Guido; Tanner, D B; Reitze, David H

2007-04-20

We describe an adaptive optical system for use as a tunable focusing element. The system provides adaptive beam shaping via controlled thermal lensing in the optical elements. The system is agile, remotely controllable, touch free, and vacuum compatible; it offers a wide dynamic range, aberration-free focal length tuning, and can provide both positive and negative lensing effects. Focusing is obtained through dynamic heating of an optical element by an external pump beam. The system is especially suitable for use in interferometric gravitational wave interferometers employing high laser power, allowing for in situ control of the laser modal properties and compensation for thermal lensing of the primary laser. Using CO(2) laser heating of fused-silica substrates, we demonstrate a focal length variable from infinity to 4.0 m, with a slope of 0.082 diopter/W of absorbed heat. For on-axis operation, no higher-order modes are introduced by the adaptive optical element. Theoretical modeling of the induced optical path change and predicted thermal lens agrees well with measurement.

Efficient electronic structure theory via hierarchical scale-adaptive coupled-cluster formalism: I. Theory and computational complexity analysis

NASA Astrophysics Data System (ADS)

Lyakh, Dmitry I.

2018-03-01

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.

Precision in ground-based solar polarimetry: simulating the role of adaptive optics.

PubMed

Krishnappa, Nagaraju; Feller, Alex

2012-11-20

Accurate measurement of polarization in spectral lines is important for the reliable inference of magnetic fields on the Sun. For ground-based observations, polarimetric precision is severely limited by the presence of Earth's atmosphere. Atmospheric turbulence (seeing) produces signal fluctuations, which combined with the nonsimultaneous nature of the measurement process cause intermixing of the Stokes parameters known as seeing-induced polarization cross talk. Previous analysis of this effect [Appl. Opt. 43, 3817 (2004)] suggests that cross talk is reduced not only with increase in modulation frequency but also by compensating the seeing-induced image aberrations by an adaptive optics (AO) system. However, in those studies the effect of higher-order image aberrations than those corrected by the AO system was not taken into account. We present in this paper an analysis of seeing-induced cross talk in the presence of higher-order image aberrations through numerical simulation. In this analysis we find that the amount of cross talk among Stokes parameters is practically independent of the degree of image aberration corrected by an AO system. However, higher-order AO corrections increase the signal-to-noise ratio by reducing the seeing caused image smearing. Further we find, in agreement with the earlier results, that cross talk is reduced considerably by increasing the modulation frequency.

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Zia, Omar

1989-01-01

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

Aerodynamic Shutoff Valve

NASA Technical Reports Server (NTRS)

Horstman, Raymond H.

1992-01-01

Aerodynamic flow achieved by adding fixed fairings to butterfly valve. When valve fully open, fairings align with butterfly and reduce wake. Butterfly free to turn, so valve can be closed, while fairings remain fixed. Design reduces turbulence in flow of air in internal suction system. Valve aids in development of improved porous-surface boundary-layer control system to reduce aerodynamic drag. Applications primarily aerospace. System adapted to boundary-layer control on high-speed land vehicles.

Methods of Adapting Digital Content for the Learning Process via Mobile Devices

ERIC Educational Resources Information Center

Lopez, J. L. Gimenez; Royo, T. Magal; Laborda, Jesus Garcia; Calvo, F. Garde

2009-01-01

This article analyses different methods of adapting digital content for its delivery via mobile devices taking into account two aspects which are a fundamental part of the learning process; on the one hand, functionality of the contents, and on the other, the actual controlled navigation requirements that the learner needs in order to acquire high…

Adaptive fuzzy logic controller with direct action type structures for InnoSAT attitude control system

NASA Astrophysics Data System (ADS)

Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.

2016-10-01

This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.

Adaptive Wavelet Coding Applied in a Wireless Control System.

PubMed

Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O

2017-12-13

Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

Measurements and performance prediction of an adaptive wing micro air vehicle

NASA Astrophysics Data System (ADS)

Shkarayev, Sergey V.; Jouse, Wayne C.; Null, William R.; Wagner, Matthew G.

2003-08-01

The mission space requirements imposed on the design of micro air vehicles (MAVs) typically consist of several distinct flight segments that generally conflict: the transit phases of flight require high speeds, while the loiter/surveillance phase requires lower flight velocities. Maximum efficiency must be sought in order to prolong battery life and aircraft endurance. The adaptive wing MAV developed at the University of Arizona features a thin, deformable flying wing with an efficient rudder-elevator control system. The wing camber is varied to accommodate different flight speeds while maintaining a constant total lift at a relatively low angle of attack. A new airfoil was developed from the Selig 5010 that features a small negative pitching moment for pitch stability. Wind tunnel tests were performed and stall angles and best lift-to-drag ratios were analyzed from the data. The wind tunnel data was used in a performance analysis in order to determine the flight speeds and throttle settings for maximum endurance at each camber, as well as the MAV's theoretical minimum and maximum flight speeds. The effectiveness of camber change on flight speed and endurance was examined with promising results; flight speed could be reduced by 25% by increasing the camber from 3 to 9% without any increase in power consumption.

Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Kun, David William

Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external disturbances such as wind gusts and turbulence. This thesis develops the ARC-LMI attitude and position controllers for an X-configuration quadrotor helicopter. The inner-loop of the autopilot controls the attitude and altitude of the quadrotor, and the outer-loop controls its position in the earth-fixed coordinate frame. Furthermore, by intelligently generating a smooth trajectory from the given reference coordinates (waypoints), the transient performance is improved. The simulation results indicate that the ARC-LMI controller design is useful for a variety of quadrotor applications, including precise trajectory tracking, autonomous waypoint navigation in the presence of disturbances, and package delivery without loss of performance.

The lifecycle of e-learning course in the adaptive educational environment

NASA Astrophysics Data System (ADS)

Gustun, O. N.; Budaragin, N. V.

2017-01-01

In the article we have considered the lifecycle model of the e-learning course in the electronic educational environment. This model consists of three stages and nine phases. In order to implement the adaptive control of the learning process we have determined the actions which are necessary to undertake at different phases of the e-learning course lifecycle. The general characteristics of the SPACEL-technology is given for creating adaptive educational environments of the next generation.

Switches of stimulus tagging frequencies interact with the conflict-driven control of selective attention, but not with inhibitory control.

PubMed

Scherbaum, Stefan; Frisch, Simon; Dshemuchadse, Maja

2016-01-01

Selective attention and its adaptation by cognitive control processes are considered a core aspect of goal-directed action. Often, selective attention is studied behaviorally with conflict tasks, but an emerging neuroscientific method for the study of selective attention is EEG frequency tagging. It applies different flicker frequencies to the stimuli of interest eliciting steady state visual evoked potentials (SSVEPs) in the EEG. These oscillating SSVEPs in the EEG allow tracing the allocation of selective attention to each tagged stimulus continuously over time. The present behavioral investigation points to an important caveat of using tagging frequencies: The flicker of stimuli not only produces a useful neuroscientific marker of selective attention, but interacts with the adaptation of selective attention itself. Our results indicate that RT patterns of adaptation after response conflict (so-called conflict adaptation) are reversed when flicker frequencies switch at once. However, this effect of frequency switches is specific to the adaptation by conflict-driven control processes, since we find no effects of frequency switches on inhibitory control processes after no-go trials. We discuss the theoretical implications of this finding and propose precautions that should be taken into account when studying conflict adaptation using frequency tagging in order to control for the described confounds. Copyright © 2015 Elsevier B.V. All rights reserved.

U.S. perspective on technology demonstration experiments for adaptive structures

NASA Technical Reports Server (NTRS)

Aswani, Mohan; Wada, Ben K.; Garba, John A.

1991-01-01

Evaluation of design concepts for adaptive structures is being performed in support of several focused research programs. These include programs such as Precision Segmented Reflector (PSR), Control Structure Interaction (CSI), and the Advanced Space Structures Technology Research Experiment (ASTREX). Although not specifically designed for adaptive structure technology validation, relevant experiments can be performed using the Passive and Active Control of Space Structures (PACOSS) testbed, the Space Integrated Controls Experiment (SPICE), the CSI Evolutionary Model (CEM), and the Dynamic Scale Model Test (DSMT) Hybrid Scale. In addition to the ground test experiments, several space flight experiments have been planned, including a reduced gravity experiment aboard the KC-135 aircraft, shuttle middeck experiments, and the Inexpensive Flight Experiment (INFLEX).

Overhead tray for cable test system

NASA Technical Reports Server (NTRS)

Saltz, K. T.

1976-01-01

System consists of overhead slotted tray, series of compatible adapter cables, and automatic test set which consists of control console and cable-switching console. System reduces hookup time and also reduces cost of fabricating and storing test cables.

Minimal-Approximation-Based Decentralized Backstepping Control of Interconnected Time-Delay Systems.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2016-12-01

A decentralized adaptive backstepping control design using minimal function approximators is proposed for nonlinear large-scale systems with unknown unmatched time-varying delayed interactions and unknown backlash-like hysteresis nonlinearities. Compared with existing decentralized backstepping methods, the contribution of this paper is to design a simple local control law for each subsystem, consisting of an actual control with one adaptive function approximator, without requiring the use of multiple function approximators and regardless of the order of each subsystem. The virtual controllers for each subsystem are used as intermediate signals for designing a local actual control at the last step. For each subsystem, a lumped unknown function including the unknown nonlinear terms and the hysteresis nonlinearities is derived at the last step and is estimated by one function approximator. Thus, the proposed approach only uses one function approximator to implement each local controller, while existing decentralized backstepping control methods require the number of function approximators equal to the order of each subsystem and a calculation of virtual controllers to implement each local actual controller. The stability of the total controlled closed-loop system is analyzed using the Lyapunov stability theorem.

Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

NASA Astrophysics Data System (ADS)

Mata-Machuca, Juan L.; Aguilar-López, Ricardo

2018-01-01

This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

Stepping reaction time and gait adaptability are significantly impaired in people with Parkinson's disease: Implications for fall risk.

PubMed

Caetano, Maria Joana D; Lord, Stephen R; Allen, Natalie E; Brodie, Matthew A; Song, Jooeun; Paul, Serene S; Canning, Colleen G; Menant, Jasmine C

2018-02-01

Decline in the ability to take effective steps and to adapt gait, particularly under challenging conditions, may be important reasons why people with Parkinson's disease (PD) have an increased risk of falling. This study aimed to determine the extent of stepping and gait adaptability impairments in PD individuals as well as their associations with PD symptoms, cognitive function and previous falls. Thirty-three older people with PD and 33 controls were assessed in choice stepping reaction time, Stroop stepping and gait adaptability tests; measurements identified as fall risk factors in older adults. People with PD had similar mean choice stepping reaction times to healthy controls, but had significantly greater intra-individual variability. In the Stroop stepping test, the PD participants were more likely to make an error (48 vs 18%), took 715 ms longer to react (2312 vs 1517 ms) and had significantly greater response variability (536 vs 329 ms) than the healthy controls. People with PD also had more difficulties adapting their gait in response to targets (poorer stepping accuracy) and obstacles (increased number of steps) appearing at short notice on a walkway. Within the PD group, higher disease severity, reduced cognition and previous falls were associated with poorer stepping and gait adaptability performances. People with PD have reduced ability to adapt gait to unexpected targets and obstacles and exhibit poorer stepping responses, particularly in a test condition involving conflict resolution. Such impaired stepping responses in Parkinson's disease are associated with disease severity, cognitive impairment and falls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

PubMed

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

NASA Astrophysics Data System (ADS)

Chen, Syuan-Yi; Gong, Sheng-Sian

2017-09-01

This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

Hydrodynamically Lubricated and Grooved Biomimetic Self-Adapting Surfaces

PubMed Central

Jackson, Robert L.; Lei, Jiang

2014-01-01

In many machines and mechanical components, there is a need for new bearing technologies to reduce friction and wear, and provide precision control of motion when the load is varied. This can be provided by electronically controlled actuators and sensors on the surfaces, but then the system reliability can be an issue. In contrast, biomimetic surfaces can be created that adapt mechanically to variations in load. This work uses numerical methods to research the use of self-adapting surfaces for bearings that are based on the deformable nature of biological materials such as articular cartilage. These surfaces are designed to change their profiles to achieve a desired behavior, without any external control. The surfaces change their profile to control the film height and tilt of the bearing to a near constant value for different loads. If the surfaces are tilted, the grooved self-adapting surfaces will also react with a larger restoring moment than a conventional grooved surface. These surfaces could be beneficial to applications where electrical systems and controls are not feasible. PMID:24956441

Hydrodynamically lubricated and grooved biomimetic self-adapting surfaces.

PubMed

Jackson, Robert L; Lei, Jiang

2014-06-04

In many machines and mechanical components, there is a need for new bearing technologies to reduce friction and wear, and provide precision control of motion when the load is varied. This can be provided by electronically controlled actuators and sensors on the surfaces, but then the system reliability can be an issue. In contrast, biomimetic surfaces can be created that adapt mechanically to variations in load. This work uses numerical methods to research the use of self-adapting surfaces for bearings that are based on the deformable nature of biological materials such as articular cartilage. These surfaces are designed to change their profiles to achieve a desired behavior, without any external control. The surfaces change their profile to control the film height and tilt of the bearing to a near constant value for different loads. If the surfaces are tilted, the grooved self-adapting surfaces will also react with a larger restoring moment than a conventional grooved surface. These surfaces could be beneficial to applications where electrical systems and controls are not feasible.

Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique.

PubMed

Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong

2016-09-01

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.

The Simulation of Magnetorheological Elastomers Adaptive Tuned Dynamic Vibration Absorber for Automobile Engine Vibration Control

NASA Astrophysics Data System (ADS)

Zhang, X. C.; Zhang, X. Z.; Li, W. H.; Liu, B.; Gong, X. L.; Zhang, P. Q.

The aim of this article is to investigate the use of a Dynamic Vibration Absorber to control vibration of engine by using simulation. Traditional means of vibration control have involved the use of passive and more recently, active methods. This study is different in that it involves an adaptive component in the design of vibration absorber using magnetorheological elastomers (MREs) as the adaptive spring. MREs are kind of novel smart material whose shear modulus can be controlled by applied magnetic field. In this paper, the vibration mode of a simple model of automobile engine is simulated by Finite Element Method (FEM) analysis. Based on the analysis, the MREs Adaptive Tuned Dynamic Vibration Absorber (ATDVA) is presented to reduce the vibration of the engine. Simulation result indicate that the control frequency of ATDVA can be changed by modifing the shear modulus of MREs and the vibraion reduction efficiency of ATDVA are also evaluated by FEM analysis.

Conflict adaptation in prefrontal cortex: now you see it, now you don't.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2014-01-01

Daily life requires people to monitor and resolve conflict arising from distracting information irrelevant to current goals. The highly influential conflict monitoring theory (CMT) holds that the anterior cingulate cortex (ACC) detects conflict and subsequently triggers the dorsolateral prefrontal cortex (DLPFC) to regulate that conflict. Multiple lines of evidence have provided support for CMT. For example, performance is faster on incongruent trials that follow other incongruent trials (iI), and is accompanied by reduced ACC and increased DLPFC activation (the conflict adaptation effect). In this fMRI study, we explored whether ACC-DLPFC conflict signaling can result in behavioral adjustments beyond on-line contexts. Participants completed a modified version of the Stroop conflict adaptation paradigm which tested for conflict adaptation effects on the current (N) trial associated with not only the immediately preceding (N - 1) trial, but also 2-back (N - 2) trials. Results demonstrated evidence for direct relationships between ACC activity on N - 2 trials and both N trial DLPFC activity and behavioral adjustment when intervening trials were congruent (i.e., icI). In contrast, when N - 1 trials were incongruent (i.e., iiI), ACC-DLPFC signaling failed and conflict adaptation was absent. These results provide new evidence demonstrating that the conflict monitor-controller maintains previously experienced conflict in the service of subsequent behavioral adjustment. However, the processing of multiple, temporally proximal conflict signals takes a toll on the working memory (WM) system, which appears to require resetting in order to adapt our behavior to frequently changing environmental demands. Copyright © 2013 Elsevier Ltd. All rights reserved.

Design of adaptive control systems by means of self-adjusting transversal filters

NASA Technical Reports Server (NTRS)

Merhav, S. J.

1986-01-01

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure.

PubMed

Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan

2014-11-01

This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.

A two-way street: bridging implementation science and cultural adaptations of mental health treatments

PubMed Central

2013-01-01

Background Racial and ethnic disparities in the United States exist along the entire continuum of mental health care, from access and use of services to the quality and outcomes of care. Efforts to address these inequities in mental health care have focused on adapting evidence-based treatments to clients’ diverse cultural backgrounds. Yet, like many evidence-based treatments, culturally adapted interventions remain largely unused in usual care settings. We propose that a viable avenue to address this critical question is to create a dialogue between the fields of implementation science and cultural adaptation. In this paper, we discuss how integrating these two fields can make significant contributions to reducing racial and ethnic disparities in mental health care. Discussion The use of cultural adaptation models in implementation science can deepen the explicit attention to culture, particularly at the client and provider levels, in implementation studies making evidence-based treatments more responsive to the needs and preferences of diverse populations. The integration of both fields can help clarify and specify what to adapt in order to achieve optimal balance between adaptation and fidelity, and address important implementation outcomes (e.g., acceptability, appropriateness). A dialogue between both fields can help clarify the knowledge, skills and roles of who should facilitate the process of implementation, particularly when cultural adaptations are needed. The ecological perspective of implementation science provides an expanded lens to examine how contextual factors impact how treatments (adapted or not) are ultimately used and sustained in usual care settings. Integrating both fields can also help specify when in the implementation process adaptations may be considered in order to enhance the adoption and sustainability of evidence-based treatments. Summary Implementation science and cultural adaptation bring valuable insights and methods to how and to what extent treatments and/or context should be customized to enhance the implementation of evidence-based treatments across settings and populations. Developing a two-way street between these two fields can provide a better avenue for moving the best available treatments into practice and for helping to reduce racial and ethnic disparities in mental health care. PMID:23958445

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-service terminal adapter based on IP technology applications in rural area

NASA Astrophysics Data System (ADS)

Gao, Li; Li, Xiaobo; Yan, Juntao; Ren, Xupeng

Take advantage of ample modern existing telecom network resources to rural areas may achieve it's information society gradually. This includes the establishment of integrated rural information service platform, modern remote education center and electronic administration management platform for rural areas. The geographical and economic constraints must be overcome for structuring the rural service support system, in order to provide technical support, information products and information services to modern rural information service system. It is important that development an access platform based IP technology, which supports multi-service access in order to implement a variety of types of mobile terminal equipment adapter access and to reduce restrictions on mobile terminal equipment.

Adding dynamic rules to self-organizing fuzzy systems

NASA Technical Reports Server (NTRS)

Buhusi, Catalin V.

1992-01-01

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Forest management under climatic and social uncertainty: trade-offs between reducing climate change impacts and fostering adaptive capacity.

PubMed

Seidl, Rupert; Lexer, Manfred J

2013-01-15

The unabated continuation of anthropogenic greenhouse gas emissions and the lack of an international consensus on a stringent climate change mitigation policy underscore the importance of adaptation for coping with the all but inevitable changes in the climate system. Adaptation measures in forestry have particularly long lead times. A timely implementation is thus crucial for reducing the considerable climate vulnerability of forest ecosystems. However, since future environmental conditions as well as future societal demands on forests are inherently uncertain, a core requirement for adaptation is robustness to a wide variety of possible futures. Here we explicitly address the roles of climatic and social uncertainty in forest management, and tackle the question of robustness of adaptation measures in the context of multi-objective sustainable forest management (SFM). We used the Austrian Federal Forests (AFF) as a case study, and employed a comprehensive vulnerability assessment framework based on ecosystem modeling, multi-criteria decision analysis, and practitioner participation. We explicitly considered climate uncertainty by means of three climate change scenarios, and accounted for uncertainty in future social demands by means of three societal preference scenarios regarding SFM indicators. We found that the effects of climatic and social uncertainty on the projected performance of management were in the same order of magnitude, underlining the notion that climate change adaptation requires an integrated social-ecological perspective. Furthermore, our analysis of adaptation measures revealed considerable trade-offs between reducing adverse impacts of climate change and facilitating adaptive capacity. This finding implies that prioritization between these two general aims of adaptation is necessary in management planning, which we suggest can draw on uncertainty analysis: Where the variation induced by social-ecological uncertainty renders measures aiming to reduce climate change impacts statistically insignificant (i.e., for approximately one third of the investigated management units of the AFF case study), fostering adaptive capacity is suggested as the preferred pathway for adaptation. We conclude that climate change adaptation needs to balance between anticipating expected future conditions and building the capacity to address unknowns and surprises. Copyright © 2012 Elsevier Ltd. All rights reserved.

CHANGES IN LEVELS OF D1, D2, OR NMDA RECEPTORS DURING WITHDRAWAL FROM BRIEF OR EXTENDED DAILY ACCESS TO IV COCAINE

PubMed Central

Ben-Shahar, Osnat; Keeley, Patrick; Cook, Mariana; Brake, Wayne; Joyce, Megan; Nyffeler, Myriel; Heston, Rebecca; Ettenberg, Aaron

2007-01-01

We previously reported that brief (1 hr), but not extended (6 hrs), daily access to cocaine results in a sensitized locomotor response to cocaine and in elevated c-Fos immunoreactivity and DAT binding in the nucleus accumbens (N.Acc) core. In order to better our understanding of the neural adaptations mediating the transition from controlled drug-use to addiction, the current experiments were set to further explore the neural adaptations resulting from these two access conditions. Rats received either brief daily access to saline or cocaine, or brief daily access followed by extended daily access, to cocaine. Subjects were then sacrificed either 20 minutes, or 14 or 60 days, after the last self-administration session. Samples of the ventral tegmental area (VTA), N.Acc core and shell, dorsal striatum, and medial prefrontal cortex (mPFC) were taken for analysis of D1 ([3H]SCH-23390), D2 ([3H]Spiperone), and NMDA ([3H]MK-801) receptor binding (using the method of receptor autoradiography). At 20 minutes into withdrawal D2 receptors were elevated and NMDA receptors were reduced in the mPFC of the brief access animals while D1 receptors were elevated in the N.Acc shell of the extended access animals, compared to saline controls. D2 receptors were reduced in the N.Acc shell of the brief access animals compared to saline controls after 14 days, and compared to extended access animals after 60 days of withdrawal. In summary, extended access to cocaine resulted in only transient changes in D1 receptors binding. These results suggest that the development of compulsive drug use is largely unrelated to changes in total binding of D2 or NMDA receptors. PMID:17161392

Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

PubMed

Bagheri, Pedram; Sun, Qiao

2016-07-01

In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Proper Orthogonal Decomposition in Optimal Control of Fluids

NASA Technical Reports Server (NTRS)

Ravindran, S. S.

1999-01-01

In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.

Position and speed control of brushless DC motors using sensorless techniques and application trends.

PubMed

Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

2010-01-01

This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks using feasibly-implementable rate adaptivity. • A buffer-management algorithm that is designed to reduce the size of router buffers, and hence energy consumed. • A packet-scheduling algorithm designed to minimize packet-processing energy requirements. Additional research is recommended in at least two areas: further exploration of rate-adaptation in network switching equipment, including incorporation of rate-adaptation in actual hardware, allowing experimentation in operational networks; and development of control protocols that allow parts of networks to be shut down while minimizing disruption to traffic flow in the network. The research is an integral part of a large effort within Bell Laboratories, Alcatel-Lucent, aimed at dramatic improvements in the energy efficiency of telecommunication networks. This Study did not explicitly consider any commercialization opportunities.« less

Based on interval type-2 fuzzy-neural network direct adaptive sliding mode control for SISO nonlinear systems

NASA Astrophysics Data System (ADS)

Lin, Tsung-Chih

2010-12-01

In this paper, a novel direct adaptive interval type-2 fuzzy-neural tracking control equipped with sliding mode and Lyapunov synthesis approach is proposed to handle the training data corrupted by noise or rule uncertainties for nonlinear SISO nonlinear systems involving external disturbances. By employing adaptive fuzzy-neural control theory, the update laws will be derived for approximating the uncertain nonlinear dynamical system. In the meantime, the sliding mode control method and the Lyapunov stability criterion are incorporated into the adaptive fuzzy-neural control scheme such that the derived controller is robust with respect to unmodeled dynamics, external disturbance and approximation errors. In comparison with conventional methods, the advocated approach not only guarantees closed-loop stability but also the output tracking error of the overall system will converge to zero asymptotically without prior knowledge on the upper bound of the lumped uncertainty. Furthermore, chattering effect of the control input will be substantially reduced by the proposed technique. To illustrate the performance of the proposed method, finally simulation example will be given.

Adaptive Control with Reference Model Modification

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

Evolutionary optimization of radial basis function classifiers for data mining applications.

PubMed

Buchtala, Oliver; Klimek, Manuel; Sick, Bernhard

2005-10-01

In many data mining applications that address classification problems, feature and model selection are considered as key tasks. That is, appropriate input features of the classifier must be selected from a given (and often large) set of possible features and structure parameters of the classifier must be adapted with respect to these features and a given data set. This paper describes an evolutionary algorithm (EA) that performs feature and model selection simultaneously for radial basis function (RBF) classifiers. In order to reduce the optimization effort, various techniques are integrated that accelerate and improve the EA significantly: hybrid training of RBF networks, lazy evaluation, consideration of soft constraints by means of penalty terms, and temperature-based adaptive control of the EA. The feasibility and the benefits of the approach are demonstrated by means of four data mining problems: intrusion detection in computer networks, biometric signature verification, customer acquisition with direct marketing methods, and optimization of chemical production processes. It is shown that, compared to earlier EA-based RBF optimization techniques, the runtime is reduced by up to 99% while error rates are lowered by up to 86%, depending on the application. The algorithm is independent of specific applications so that many ideas and solutions can be transferred to other classifier paradigms.

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

Wavefront error budget development for the Thirty Meter Telescope laser guide star adaptive optics system

NASA Astrophysics Data System (ADS)

Gilles, Luc; Wang, Lianqi; Ellerbroek, Brent

2008-07-01

This paper describes the modeling effort undertaken to derive the wavefront error (WFE) budget for the Narrow Field Infrared Adaptive Optics System (NFIRAOS), which is the facility, laser guide star (LGS), dual-conjugate adaptive optics (AO) system for the Thirty Meter Telescope (TMT). The budget describes the expected performance of NFIRAOS at zenith, and has been decomposed into (i) first-order turbulence compensation terms (120 nm on-axis), (ii) opto-mechanical implementation errors (84 nm), (iii) AO component errors and higher-order effects (74 nm) and (iv) tip/tilt (TT) wavefront errors at 50% sky coverage at the galactic pole (61 nm) with natural guide star (NGS) tip/tilt/focus/astigmatism (TTFA) sensing in J band. A contingency of about 66 nm now exists to meet the observatory requirement document (ORD) total on-axis wavefront error of 187 nm, mainly on account of reduced TT errors due to updated windshake modeling and a low read-noise NGS wavefront sensor (WFS) detector. A detailed breakdown of each of these top-level terms is presented, together with a discussion on its evaluation using a mix of high-order zonal and low-order modal Monte Carlo simulations.

Enhancement of "Reducing the Risk" for the 21st Century: Improvement to a Curriculum Developed to Prevent Teen Pregnancy and STI Transmission

ERIC Educational Resources Information Center

Langley, Cheri; Barbee, Anita P.; Antle, Becky; Christensen, Dana; Archuleta, Adrian; Sar, Bibhuti K.; Karam, Eli; van Zyl, Riaan; Cunningham, Michael R.; Borders, Kevin

2015-01-01

To ensure that "Reducing the Risk," a successful teen pregnancy prevention education curriculum, remains relevant for today's youth, covers all information youth need to know in order to make better choices, and is delivered in a standardized way, adaptations were made and enhancements were added. This article describes results of a…

Sensorless control of ship propulsion interior permanent magnet synchronous motor based on a new sliding mode observer.

PubMed

Ren, Jun-Jie; Liu, Yan-Cheng; Wang, Ning; Liu, Si-Yuan

2015-01-01

This paper proposes a sensorless speed control strategy for ship propulsion interior permanent magnet synchronous motor (IPMSM) based on a new sliding-mode observer (SMO). In the SMO the low-pass filter and the method of arc-tangent calculation of extended electromotive force (EMF) or phase-locked loop (PLL) technique are not used. The calculation of the rotor speed is deduced from the Lyapunov function stability analysis. In order to reduce system chattering, sigmoid functions with switching gains being adaptively updated by fuzzy logic systems are innovatively incorporated into the SMO. Finally, simulation results for a 4.088 MW ship propulsion IPMSM and experimental results from a 7.5 kW IPMSM drive are provided to verify the effectiveness of the proposed SMO method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

SPOT4 Operational Control Center (CMP)

NASA Technical Reports Server (NTRS)

Zaouche, G.

1993-01-01

CNES(F) is responsible for the development of a new generation of Operational Control Center (CMP) which will operate the new heliosynchronous remote sensing satellite (SPOT4). This Operational Control Center takes large benefit from the experience of the first generation of control center and from the recent advances in computer technology and standards. The CMP is designed for operating two satellites all the same time with a reduced pool of controllers. The architecture of this CMP is simple, robust, and flexible, since it is based on powerful distributed workstations interconnected through an Ethernet LAN. The application software uses modern and formal software engineering methods, in order to improve quality and reliability, and facilitate maintenance. This software is table driven so it can be easily adapted to other operational needs. Operation tasks are automated to the maximum extent, so that it could be possible to operate the CMP automatically with very limited human interference for supervision and decision making. This paper provides an overview of the SPOTS mission and associated ground segment. It also details the CMP, its functions, and its software and hardware architecture.

Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.

PubMed

Xie, Yuanlong; Tang, Xiaoqi; Song, Bao; Zhou, Xiangdong; Guo, Yixuan

2018-04-01

In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts. The proposed method directly exploits the closed-loop process data for the AFOPI controller design under unknown noise distribution and data missing probability. Firstly, the proposed method constructs the AFOPI controller tuning problem as a parameter identification problem using the modified l p norm virtual reference feedback tuning (VRFT). Then, iteratively reweighted least squares is integrated into the l p norm VRFT to give a consistent compensation solution for the AFOPI controller. The measurement noise and data dropouts are estimated and eliminated by feedback compensation periodically, so that the AFOPI controller is updated online to accommodate the time-varying operating conditions. Moreover, the convergence and stability are guaranteed by mathematical analysis. Finally, the effectiveness of the proposed method is demonstrated both on simulations and experiments implemented on a practical PMSM servo system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Startle reduces recall of a recently learned internal model.

PubMed

Wright, Zachary; Patton, James L; Ravichandran, Venn

2011-01-01

Recent work has shown that preplanned motor programs are released early from subcortical areas by the using a startling acoustic stimulus (SAS). Our question is whether this response might also contain a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Studies of adaptation to robotic forces have shown some evidence of this, but were potentially confounded by cocontraction caused by startle. We performed a new adaptation experiment using a visually distorted field that could not be confounded by cocontraction. We found that in all subjects that exhibited startle, the startle stimulus (1) reduced performance of the recently learned task (2) reduced after-effect magnitudes. Because startle reduced but did not eliminate the recall of learned control, we suggest that multiple neural centers (cortical and subcortical) are involved in such learning and adaptation, which can impact training areas such as piloting, teleoperation, sports, and rehabilitation. © 2011 IEEE

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

Advances in adaptive control theory: Gradient- and derivative-free approaches

NASA Astrophysics Data System (ADS)

Yucelen, Tansel

In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures. We first present a novel Kalman filter based approach for approximately enforcing a linear constraint in standard adaptive control design. One application is that this leads to alternative forms for well known modification terms such as e-modification. In addition, it leads to smaller tracking errors without incurring significant oscillations in the system response and without requiring high modification gain. We derive alternative forms of e- and adaptive loop recovery (ALR-) modifications. Next, we show how to use Kalman filter optimization to derive a novel adaptation law. This results in an optimization-based time-varying adaptation gain that reduces the need for adaptation gain tuning. A second major contribution of this dissertation is the development of a novel derivative-free, delayed weight update law for adaptive control. The assumption of constant unknown ideal weights is relaxed to the existence of time-varying weights, such that fast and possibly discontinuous variation in weights are allowed. This approach is particulary advantageous for applications to systems that can undergo a sudden change in dynamics, such as might be due to reconfiguration, deployment of a payload, docking, or structural damage, and for rejection of external disturbance processes. As a third and final contribution, we develop a novel approach for extending all the methods developed in this dissertation to the case of output feedback. The approach is developed only for the case of derivative-free adaptive control, and the extension of the other approaches developed previously for the state feedback case to output feedback is left as a future research topic. The proposed approaches of this dissertation are illustrated in both simulation and flight test.

Adaptive optics vision simulation and perceptual learning system based on a 35-element bimorph deformable mirror.

PubMed

Dai, Yun; Zhao, Lina; Xiao, Fei; Zhao, Haoxin; Bao, Hua; Zhou, Hong; Zhou, Yifeng; Zhang, Yudong

2015-02-10

An adaptive optics visual simulation combined with a perceptual learning (PL) system based on a 35-element bimorph deformable mirror (DM) was established. The larger stroke and smaller size of the bimorph DM made the system have larger aberration correction or superposition ability and be more compact. By simply modifying the control matrix or the reference matrix, select correction or superposition of aberrations was realized in real time similar to a conventional adaptive optics closed-loop correction. PL function was first integrated in addition to conventional adaptive optics visual simulation. PL training undertaken with high-order aberrations correction obviously improved the visual function of adult anisometropic amblyopia. The preliminary application of high-order aberrations correction with PL training on amblyopia treatment was being validated with a large scale population, which might have great potential in amblyopia treatment and visual performance maintenance.

Studying the Global Bifurcation Involving Wada Boundary Metamorphosis by a Method of Generalized Cell Mapping with Sampling-Adaptive Interpolation

NASA Astrophysics Data System (ADS)

Liu, Xiao-Ming; Jiang, Jun; Hong, Ling; Tang, Dafeng

In this paper, a new method of Generalized Cell Mapping with Sampling-Adaptive Interpolation (GCMSAI) is presented in order to enhance the efficiency of the computation of one-step probability transition matrix of the Generalized Cell Mapping method (GCM). Integrations with one mapping step are replaced by sampling-adaptive interpolations of third order. An explicit formula of interpolation error is derived for a sampling-adaptive control to switch on integrations for the accuracy of computations with GCMSAI. By applying the proposed method to a two-dimensional forced damped pendulum system, global bifurcations are investigated with observations of boundary metamorphoses including full to partial and partial to partial as well as the birth of fully Wada boundary. Moreover GCMSAI requires a computational time of one thirtieth up to one fiftieth compared to that of the previous GCM.

Parallel Adaptive Mesh Refinement for High-Order Finite-Volume Schemes in Computational Fluid Dynamics

NASA Astrophysics Data System (ADS)

Schwing, Alan Michael

For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable comparisons across a range of regimes. Unsteady and steady applications are considered in both subsonic and supersonic flows. Inviscid and viscous simulations achieve similar results at a much reduced cost when employing dynamic mesh adaptation. Several techniques for guiding adaptation are compared. Detailed analysis of statistics from the instrumented solver enable understanding of the costs associated with adaptation. Adaptive mesh refinement shows promise for the test cases presented here. It can be considerably faster than using conventional grids and provides accurate results. The procedures for adapting the grid are light-weight enough to not require significant computational time and yield significant reductions in grid size.

Active Suppression of Instabilities in Engine Combustors

NASA Technical Reports Server (NTRS)

Kopasakis, George

2004-01-01

A method of feedback control has been proposed as a means of suppressing thermo-acoustic instabilities in a liquid- fueled combustor of a type used in an aircraft engine. The basic principle of the method is one of (1) sensing combustor pressure oscillations associated with instabilities and (2) modulating the rate of flow of fuel to the combustor with a control phase that is chosen adaptively so that the pressure oscillations caused by the modulation oppose the sensed pressure oscillations. The need for this method arises because of the planned introduction of advanced, lean-burning aircraft gas turbine engines, which promise to operate with higher efficiencies and to emit smaller quantities of nitrogen oxides, relative to those of present aircraft engines. Unfortunately, the advanced engines are more susceptible to thermoacoustic instabilities. These instabilities are hard to control because they include large dead-time phase shifts, wide-band noise characterized by amplitudes that are large relative to those of the instabilities, exponential growth of the instabilities, random net phase walks, and amplitude fluctuations. In this method (see figure), the output of a combustion-pressure sensor would be wide-band-pass filtered and then further processed to generate a control signal that would be applied to a fast-actuation valve to modulate the flow of fuel. Initially, the controller would rapidly take large phase steps in order to home in, within a fraction of a second, to a favorable phase region within which the instability would be reduced. Then the controller would restrict itself to operate within this phase region and would further restrict itself to operate within a region of stability, as long as the power in the instability signal was decreasing. In the phase-shifting scheme of this method, the phase of the control vector would be made to continuously bounce back and forth from one boundary of an effective stability region to the other. Computationally, this scheme would be implemented by the adaptive sliding phaser averaged control (ASPAC) algorithm, which requires very little detailed knowledge of the combustor dynamics. In the ASPAC algorithm, the power of the instability signal would be calculated from the wide-bandpass- filtered combustion-pressure signal and averaged over a period of time (typically of the order of a few hundredths of a second) corresponding to the controller updating cycle [not to be confused with the controller sampling cycle, which would be much shorter (typically of the order of 10(exp -4) second)].

Synthesis of the adaptive continuous system for the multi-axle wheeled vehicle body oscillation damping

NASA Astrophysics Data System (ADS)

Zhileykin, M. M.; Kotiev, G. O.; Nagatsev, M. V.

2018-02-01

In order to meet the growing mobility requirements for the wheeled vehicles on all types of terrain the engineers have to develop a large number of specialized control algorithms for the multi-axle wheeled vehicle (MWV) suspension improving such qualities as ride comfort, handling and stability. The authors have developed an adaptive algorithm of the dynamic damping of the MVW body oscillations. The algorithm provides high ride comfort and high mobility of the vehicle. The article discloses a method for synthesis of an adaptive dynamic continuous algorithm of the MVW body oscillation damping and provides simulation results proving high efficiency of the developed control algorithm.

Adaptive antenna arrays for weak interfering signals. [in satellite communication

NASA Technical Reports Server (NTRS)

Gupta, I. J.; Ksienski, A. A.

1986-01-01

It is shown that conventional adaptive arrays are unable to suppress weak interfering signals. To overcome this problem, the feedback loops controlling the array weights were modified, reducing the noise level by reducing the correlation between the noise components of the two inputs to the loop correlator. Various techniques to decorrelate these noise components are discussed. An expression is derived for the amount of noise decorrelation required to achieve a specified interference suppression. The results are of interest in connection with satellite communications.

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

NASA Astrophysics Data System (ADS)

Chen, Jiaxi; Li, Junmin

2018-02-01

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T-S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Real-Time Wavefront Control for the PALM-3000 High Order Adaptive Optics System

NASA Technical Reports Server (NTRS)

Truong, Tuan N.; Bouchez, Antonin H.; Dekany, Richard G.; Guiwits, Stephen R.; Roberts, Jennifer E.; Troy, Mitchell

2008-01-01

We present a cost-effective scalable real-time wavefront control architecture based on off-the-shelf graphics processing units hosted in an ultra-low latency, high-bandwidth interconnect PC cluster environment composed of modules written in the component-oriented language of nesC. The architecture enables full-matrix reconstruction of the wavefront at up to 2 KHz with latency under 250 us for the PALM-3000 adaptive optics systems, a state-of-the-art upgrade on the 5.1 meter Hale Telescope that consists of a 64 x 64 subaperture Shack-Hartmann wavefront sensor and a 3368 active actuator high order deformable mirror in series with a 241 active actuator tweeter DM. The architecture can easily scale up to support much larger AO systems at higher rates and lower latency.

Super-Gaussian laser intensity output formation by means of adaptive optics

NASA Astrophysics Data System (ADS)

Cherezova, T. Y.; Chesnokov, S. S.; Kaptsov, L. N.; Kudryashov, A. V.

1998-10-01

An optical resonator using an intracavity adaptive mirror with three concentric rings of controlling electrodes, which produc low loss and large beamwidth super-Gaussian output of order 4, 6, 8, is analyzed. An inverse propagation method is used to determine the appropriate shape of the adaptive mirror. The mirror reproduces the shape with minimal RMS error by combining weights of experimentally measured response functions of the mirror sample. The voltages applied to each mirror electrode are calculated. Practical design parameters such as construction of an adaptive mirror, Fresnel numbers, and geometric factor are discussed.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

Developing eco-adaptive cruise control systems.

DOT National Transportation Integrated Search

2014-01-01

The study demonstrates the feasibility of two eco-driving applications which reduces vehicle fuel consumption and greenhouse gas emissions. In particular, the study develops an eco-drive system that combines eco-cruise control logic with state-of-the...

Identifying partial topology of complex dynamical networks via a pinning mechanism

NASA Astrophysics Data System (ADS)

Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

2018-04-01

In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

Comparison of a brain-based adaptive system and a manual adaptable system for invoking automation.

PubMed

Bailey, Nathan R; Scerbo, Mark W; Freeman, Frederick G; Mikulka, Peter J; Scott, Lorissa A

2006-01-01

Two experiments are presented examining adaptive and adaptable methods for invoking automation. Empirical investigations of adaptive automation have focused on methods used to invoke automation or on automation-related performance implications. However, no research has addressed whether performance benefits associated with brain-based systems exceed those in which users have control over task allocations. Participants performed monitoring and resource management tasks as well as a tracking task that shifted between automatic and manual modes. In the first experiment, participants worked with an adaptive system that used their electroencephalographic signals to switch the tracking task between automatic and manual modes. Participants were also divided between high- and low-reliability conditions for the system-monitoring task as well as high- and low-complacency potential. For the second experiment, participants operated an adaptable system that gave them manual control over task allocations. Results indicated increased situation awareness (SA) of gauge instrument settings for individuals high in complacency potential using the adaptive system. In addition, participants who had control over automation performed more poorly on the resource management task and reported higher levels of workload. A comparison between systems also revealed enhanced SA of gauge instrument settings and decreased workload in the adaptive condition. The present results suggest that brain-based adaptive automation systems may enhance perceptual level SA while reducing mental workload relative to systems requiring user-initiated control. Potential applications include automated systems for which operator monitoring performance and high-workload conditions are of concern.

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Measurement of specimen-induced aberrations of biological samples using phase stepping interferometry.

PubMed

Schwertner, M; Booth, M J; Neil, M A A; Wilson, T

2004-01-01

Confocal or multiphoton microscopes, which deliver optical sections and three-dimensional (3D) images of thick specimens, are widely used in biology. These techniques, however, are sensitive to aberrations that may originate from the refractive index structure of the specimen itself. The aberrations cause reduced signal intensity and the 3D resolution of the instrument is compromised. It has been suggested to correct for aberrations in confocal microscopes using adaptive optics. In order to define the design specifications for such adaptive optics systems, one has to know the amount of aberrations present for typical applications such as with biological samples. We have built a phase stepping interferometer microscope that directly measures the aberration of the wavefront. The modal content of the wavefront is extracted by employing Zernike mode decomposition. Results for typical biological specimens are presented. It was found for all samples investigated that higher order Zernike modes give only a small contribution to the overall aberration. Therefore, these higher order modes can be neglected in future adaptive optics sensing and correction schemes implemented into confocal or multiphoton microscopes, leading to more efficient designs.

Adaptive choice between articulatory rehearsal and attentional refreshing in verbal working memory.

PubMed

Camos, Valérie; Mora, Gerome; Oberauer, Klaus

2011-02-01

Because both articulatory rehearsal and attentional refreshing aid in the maintenance of verbal information in the short term, the present study evaluated the adaptive use of these mechanisms, using a complex span paradigm. In Experiment 1, the phonological similarity of memory list words and the attentional demand of concurrent processing were manipulated. As was predicted, a phonological similarity effect (PSE) appeared only when the concurrent task was attention demanding, thus impairing the use of refreshing and encouraging rehearsal. To verify that PSE indicates the use of rehearsal, participants were instructed to use one of the two mechanisms in Experiments 2 and 3. In accordance wih Experiment 1, the PSE was observed only under rehearsal. Thus, adults could adaptively choose between the two mechanisms. When remembering phonologically confusable materials, they prefer refreshing in order to reduce the impact of phonological characteristics. When available attention is reduced, they favor a less attention-demanding mechanism, rehearsal.

LQG control of a deformable mirror adaptive optics system with time-delayed measurements

NASA Astrophysics Data System (ADS)

Anderson, David J.

1991-12-01

This thesis proposes a linear quadratic Gaussian (LQG) control law for a ground-based deformable mirror adaptive optics system. The incoming image wavefront is distorted, primarily in phase, due to the turbulent effects of the earth's atmosphere. The adaptive optics system attempts to compensate for the distortion with a deformable mirror. A Hartman wavefront sensor measures the degree of distortion in the image wavefront. The measurements are input to a Kalman filter which estimates the system states. The state estimates are processed by a linear quadratic regulator which generates the appropriate control voltages to apply to the deformable mirror actuators. The dynamics model for the atmospheric phase distortion consists of 14 Zernike coefficient states; each modeled as a first-order linear time-invariant shaping filter driven by zero-mean white Gaussian noise. The dynamics of the deformable mirror are also model as 14 Zernike coefficients with first-order deterministic dynamics. A significant reduction in total wavefront phase distortion is achieved in the presence of time-delayed measurements. Wavefront sensor sampling rate is the major factor limiting system performance. The Multimode Simulation for Optimal Filter Evaluation (MSOFE) software is the performance evaluation tool of choice for this research.

Calibrating and adjusting expectations in life: A grounded theory on how elderly persons with somatic health problems maintain control and balance in life and optimize well-being

PubMed Central

Helvik, Anne-Sofie; Iversen, Valentina Cabral; Steiring, Randi; Hallberg, Lillemor R-M

2011-01-01

Aim This study aims at exploring the main concern for elderly individuals with somatic health problems and what they do to manage this. Method In total, 14 individuals (mean=74.2 years; range=68–86 years) of both gender including hospitalized and outpatient persons participated in the study. Open interviews were conducted and analyzed according to grounded theory, an inductive theory-generating method. Results The main concern for the elderly individuals with somatic health problems was identified as their striving to maintain control and balance in life. The analysis ended up in a substantive theory explaining how elderly individuals with somatic disease were calibrating and adjusting their expectations in life in order to adapt to their reduced energy level, health problems, and aging. By adjusting the expectations to their actual abilities, the elderly can maintain a sense of that they still have the control over their lives and create stability. The ongoing adjustment process is facilitated by different strategies and result despite lower expectations in subjective well-being. The facilitating strategies are utilizing the network of important others, enjoying cultural heritage, being occupied with interests, having a mission to fulfill, improving the situation by limiting boundaries and, finally, creating meaning in everyday life. Conclusion The main concern of the elderly with somatic health problems was to maintain control and balance in life. The emerging theory explains how elderly people with somatic health problems calibrate their expectations of life in order to adjust to reduced energy, health problems, and aging. This process is facilitated by different strategies and result despite lower expectation in subjective well-being. PMID:21468299

Adaptation of water resource systems to an uncertain future

NASA Astrophysics Data System (ADS)

Walsh, C. L.; Blenkinsop, S.; Fowler, H. J.; Burton, A.; Dawson, R. J.; Glenis, V.; Manning, L. J.; Kilsby, C. G.

2015-09-01

Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days, and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth the median number of drought order occurrences may increase five-fold. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence a portfolio of measures are required.

Cultural adaptation of an intervention to reduce sexual risk behaviors among patients attending a STI clinic in St. Petersburg, Russia.

PubMed

Grau, Lauretta E; Krasnoselskikh, Tatiana V; Shaboltas, Alla V; Skochilov, Roman V; Kozlov, Andrei P; Abdala, Nadia

2013-08-01

Cultural adaptation is an important step in the process of implementing health promotion interventions that, having been proven to be effective in one culture, are being applied in another. This study describes the results of a formative investigation to culturally adapt a STI/HIV risk reduction intervention for use in St. Petersburg, Russia. Analyses of data from brief elicitation interviews, focus groups, community experts, and a pilot test of the adapted intervention identified environmental, cognitive-information processing, and affect-motivation factors that needed to be addressed during the adaptation process. The participant/counselor relationship was adapted to reflect a hierarchical (cf. collaborative) relationship in order to accommodate Russian expectations about patient interactions with healthcare experts. Key skills building activities (e.g., identification of personal risk behaviors, role-playing) were approached gradually or indirectly in order to maintain participants' engagement in the intervention, and close-ended questions were added to assist participants in understanding unfamiliar concepts such as "triggers" and self-efficacy. Information about the prevalence of HIV/STI infections and alcohol use included data specific to St. Petersburg to increase the personal relevance of these materials and messages. Intervention components were tailored to participants' risk reduction and informational needs. No gender differences that would have justified adaptation of the intervention approach or content were noted. Examples of specific adaptations and the key issues to attend to when adapting behavioral interventions for use in Russian clinical settings are discussed.

Feed-forward adaptive-optic correction of a weakly-compressible high-subsonic shear layer

NASA Astrophysics Data System (ADS)

Duffin, Daniel A.

Development of airborne laser systems began in the 1970s with the Airborne Laser Laboratory, a KC135 aircraft with a CO2 laser projected from a beam director mounted atop the aircraft as a hemispherical turret encased in a fairing. It was known that the turbulent air flowing around the turret and separating over the aft portions of the turret would aberrate the laser beam's wavefront (the aero-optic problem); however, the CO2 wavelength, 10.6 mum, was long enough that the aberrating turbulent flow decreased the system's performance by only about 5%. With newer airborne laser systems using wavelengths nearer 1 mum, this same turbulent flow now reduces system performance by more than 95%. It has long been known that if a conjugate waveform is used to pre-distort the outgoing laser's wavefront, the turbulence will actually correct the beam, restoring most of the system's performance. The problem with performing this compensation is that the system for performing this function, the so-called adaptive-optic system, is bandwidth limited in its conventional architecture, by orders of magnitude lower than that required to correct for the aero-optic effects. The research described in this dissertation explored changing the adaptive-optic paradigm from feedback to feed-forward by adding flow control to make the aberration environment predictable rather than unpredictable. This research demonstrated that the turbulent high-speed separated shear layer could be robustly forced into a regularized form. It was also shown that these regularized velocity patterns in the shear layer produced periodic optical aberrations. Extensive measurement and analysis of these convecting aberrations yielded the underlying structure required to produce the conjugate wavefront correction patterns required for a range of laser propagation angles through the shear layer. Ultimately, a feed-forward adaptive-optic system was developed and used to demonstrate the highest-bandwidth correction of aero-optic aberrations ever performed; the effective bandwidth of the demonstrated adaptive-optic correction was at least two orders of magnitude greater than the capabilities of existing conventional adaptive-optic systems.

High-Resolution Adaptive Optics Test-Bed for Vision Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilks, S C; Thomspon, C A; Olivier, S S

2001-09-27

We discuss the design and implementation of a low-cost, high-resolution adaptive optics test-bed for vision research. It is well known that high-order aberrations in the human eye reduce optical resolution and limit visual acuity. However, the effects of aberration-free eyesight on vision are only now beginning to be studied using adaptive optics to sense and correct the aberrations in the eye. We are developing a high-resolution adaptive optics system for this purpose using a Hamamatsu Parallel Aligned Nematic Liquid Crystal Spatial Light Modulator. Phase-wrapping is used to extend the effective stroke of the device, and the wavefront sensing and wavefrontmore » correction are done at different wavelengths. Issues associated with these techniques will be discussed.« less

Letting thoughts take wing.

PubMed

Jorgensen, Chuck; Wheeler, Kevin

2002-03-01

Recent developments in neuroelectronics are applied to aviation and airplane flight control instruments. Electromyographic control has been applied to flight simulations using the autopilot interface in order to use gestures to give bank and pitch commands to the autopilot. In other demonstrations, direct rate control was used to perform repeated successful landings and the damage-adaptive capability of inner-loop neural and propulsion-based controls was utilized.

Wavefront control system for the Keck telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brase, J. M., LLNL

1998-03-01

The laser guide star adaptive optics system currently being developed for the Keck 2 telescope consists of several major subsystems: the optical bench, wavefront control, user interface and supervisory control, and the laser system. The paper describes the design and implementation of the wavefront control subsystem that controls a 349 actuator deformable mirror for high order correction and tip-tilt mirrors for stabilizing the image and laser positions.

Adaptive Variable Bias Magnetic Bearing Control

NASA Technical Reports Server (NTRS)

Johnson, Dexter; Brown, Gerald V.; Inman, Daniel J.

1998-01-01

Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.