Convergence performance comparisons of PID, MRAC, and PID + MRAC hybrid controller
NASA Astrophysics Data System (ADS)
Zhang, Dan; Wei, Bin
2016-06-01
This study proposes a hybrid controller by combining a proportional-integral-derivative (PID) control and a model reference adaptive control (MRAC), which named as PID + MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID + MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID + MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.
Convergence performance comparisons of PID, MRAC, and PID + MRAC hybrid controller
NASA Astrophysics Data System (ADS)
Zhang, Dan; Wei, Bin
2016-05-01
This study proposes a hybrid controller by combining a proportional-integral-derivative (PID) control and a model reference adaptive control (MRAC), which named as PID + MRAC controller. The convergence performances of the PID control, MRAC, and hybrid PID + MRAC are also compared. Through the simulation in Matlab, the results show that the convergence speed and performance of the MRAC and the PID + MRAC controller are better than those of the PID controller. In addition, the convergence performance of the hybrid control is better than that of the MRAC control.
MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft
Xu, Xieyu; Yang, Lingyu; Zhang, Jing
2015-01-01
This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. PMID:26180839
Method For Model-Reference Adaptive Control
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1990-01-01
Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.
Adaptive Modal Identification for Flutter Suppression Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.
2016-01-01
In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.
On the Robustness Properties of M-MRAC
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram
2012-01-01
The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.
Input and Output Performance of M-MRAC in the Presence of Bounded Disturbances
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje Srinvas
2011-01-01
This paper presents performance analysis of novel modified model reference adaptive control (M-MRAC) architecture in conjunction with different robust adaptive laws for the uncertain linear systems subject to unknown but bounded disturbances. It is shown that for any robust adaptive law the tracking error of the M-MRAC system can be arbitrarily decreased in transient and in the steady-state by increasing the adaptation rate, without generating high frequency oscillations in the control signal, which are unavoidable in conventional MRAC systems for large adaptation rates. Moreover, the generated adaptive control signal arbitrary closely tracks the ideal control signal when the error feedback gain is simultaneously increased with the adaptation rate, according to derived rule. The results are demonstrated via simulations.
Accommodating Sensor Bias in MRAC for State Tracking
NASA Technical Reports Server (NTRS)
Patre, Parag; Joshi, Suresh M.
2011-01-01
The problem of accommodating unknown sensor bias is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor faults can occur during operation, and if the biased state measurements are directly used with a standard MRAC control law, neither closed-loop signal boundedness, nor asymptotic tracking can be guaranteed and the resulting tracking errors may be unbounded or unacceptably large. A modified MRAC law is proposed, which combines a bias estimator with control gain adaptation, and it is shown that signal boundedness can be accomplished, although the tracking error may not go to zero. Further, for the case wherein an asymptotically stable sensor bias estimator is available, an MRAC control law is proposed to accomplish asymptotic tracking and signal boundedness. Such a sensor bias estimator can be designed if additional sensor measurements are available, as illustrated for the case wherein bias is present in the rate gyro and airspeed measurements. Numerical example results are presented to illustrate each of the schemes.
MRAC Revisited: Guaranteed Performance with Reference Model Modification
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmaje
2010-01-01
This paper presents modification of the conventional model reference adaptive control (MRAC) architecture in order to achieve guaranteed transient performance both in the output and input signals of an uncertain system. The proposed modification is based on the tracking error feedback to the reference model. It is shown that approach guarantees tracking of a given command and the ideal control signal (one that would be designed if the system were known) not only asymptotically but also in transient by a proper selection of the error feedback gain. The method prevents generation of high frequency oscillations that are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference command of any magnitude form any initial position without re-tuning. The benefits of the method are demonstrated in simulations.
M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje
2015-01-01
The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.
Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures
NASA Technical Reports Server (NTRS)
Joshi, Suresh M.
2012-01-01
The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.
Adaptive control of robotic manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.
NASA Astrophysics Data System (ADS)
Tu, Jianwei; Lin, Xiaofeng; Tu, Bo; Xu, Jiayun; Tan, Dongmei
2014-09-01
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.
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
Analytical and experimental study of control effort associated with model reference adaptive control
NASA Technical Reports Server (NTRS)
Messer, R. S.; Haftka, R. T.; Cudney, H. H.
1992-01-01
Numerical simulation results presently obtained for the performance of model reference adaptive control (MRAC) are experimentally verified, with a view to accounting for differences between the plant and the reference model after the control function has been brought to bear. MRAC is both experimentally and analytically applied to a single-degree-of-freedom system, as well as analytically to a MIMO system having controlled differences between the reference model and the plant. The control effort is noted to be sensitive to differences between the plant and the reference model.
Model reference adaptive control of robots
NASA Technical Reports Server (NTRS)
Steinvorth, Rodrigo
1991-01-01
This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.
Direct model reference adaptive control of a flexible robotic manipulator
NASA Technical Reports Server (NTRS)
Meldrum, D. R.
1985-01-01
Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.
Dynamics modeling and adaptive control of flexible manipulators
NASA Technical Reports Server (NTRS)
Sasiadek, J. Z.
1991-01-01
An application of Model Reference Adaptive Control (MRAC) to the position and force control of flexible manipulators and robots is presented. A single-link flexible manipulator is analyzed. The problem was to develop a mathematical model of a flexible robot that is accurate. The objective is to show that the adaptive control works better than 'conventional' systems and is suitable for flexible structure control.
NASA Technical Reports Server (NTRS)
Schaefer, Jacob; Hanson, Curt; Johnson, Marcus A.; Nguyen, Nhan
2011-01-01
Three model reference adaptive controllers (MRAC) with varying levels of complexity were evaluated on a high performance jet aircraft and compared along with a baseline nonlinear dynamic inversion controller. The handling qualities and performance of the controllers were examined during failure conditions that induce coupling between the pitch and roll axes. Results from flight tests showed with a roll to pitch input coupling failure, the handling qualities went from Level 2 with the baseline controller to Level 1 with the most complex MRAC tested. A failure scenario with the left stabilator frozen also showed improvement with the MRAC. Improvement in performance and handling qualities was generally seen as complexity was incrementally added; however, added complexity usually corresponds to increased verification and validation effort required for certification. The tradeoff between complexity and performance is thus important to a controls system designer when implementing an adaptive controller on an aircraft. This paper investigates this relation through flight testing of several controllers of vary complexity.
Higher order direct model reference adaptive control with generic uniform ultimate boundedness
NASA Astrophysics Data System (ADS)
Maity, Arnab; Höcht, Leonhard; Holzapfel, Florian
2015-10-01
This paper proposes a new higher order model reference adaptive control (HO-MRAC) approach following direct adaptive control philosophy, which estimates unknown time-varying parameters. This approach leads to a Lyapunov based conventional MRAC update law, augmented by an observer type parameter predictor dynamics. The predictor dynamics are composed of a stable known part, a feedback of the parameter error and unknown higher order parameters, which are updated using a Lyapunov based adaptive design. So, this HO-MRAC can cope with rapidly changing parameters, due to estimation of their time derivatives. Moreover, for stability analysis, a Lyapunov based generic ultimate boundedness theorem is presented, which allows for a computation of separate bounds for each state vector partition. Furthermore, this theorem formulates the explicit specification of transient and ultimate bounds, reaching time on the ultimate bounds and a set of admissible initial conditions. Two challenging illustrative examples demonstrate the effectiveness of the proposed approach.
Model reference adaptive control of flexible robots in the presence of sudden load changes
NASA Astrophysics Data System (ADS)
Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory W.
1991-02-01
Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition such MRAC procedures are designed so that a feedforward augmented output follows the reference model output thus resulting in an ultimately bounded rather than zero output error. Thus modifications are suggested and tested that 1)incorporate feedforward into the reference model''s output as well as the plant''s output and 2)incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error and thus encourage further use of MRAC for more complex flexible robotic systems.
NASA Technical Reports Server (NTRS)
Lubin, Philip M.; Tomizuka, Masayoshi; Chingcuanco, Alfredo O.; Meinhold, Peter R.
1991-01-01
A balloon-born stabilized platform has been developed for the remotely operated altitude-azimuth pointing of a millimeter wave telescope system. This paper presents a development and implementation of model reference adaptive control (MRAC) for the azimuth-pointing system of the stabilized platform. The primary goal of the controller is to achieve pointing rms better than 0.1 deg. Simulation results indicate that MRAC can achieve pointing rms better than 0.1 deg. Ground test results show pointing rms better than 0.03 deg. Data from the first flight at the National Scientific Balloon Facility (NSBF) Palestine, Texas show pointing rms better than 0.02 deg.
Model reference adaptive control -- Implementation considerations on an integer-based DSP
Chen, L.; Balda, J.C.; Olejniczak, K.J.
1995-12-31
Model Reference Adaptive Control (MRAC) techniques may be used in high-performance applications of induction-motor (IM) drives to minimize adverse effects from changes in the load conditions and/or system parameters. Although the MRAC technique accounts for uncertainties and/or inaccuracies of the motor and load parameters in the design stage, its implementation on an integer-based Digital Signal Processor (DSP) has several difficulties associated with the large dynamic range of the covariance matrix and the finite length of the DSP word. This paper addresses the solution to these difficulties using double-word fixed-point algorithms which increase the dynamic range of the data and concurrently reduces rounding and/or truncation errors. The unavoidable disadvantage is a longer execution time. First, the general MRAC technique is briefly discussed for reference. Double-word fixed-point addition, subtraction, multiplication and division are then described in detail. Finally, experimental results are presented to illustrate the proposed ideas when controlling the speed of a 2-hp IM using the proposed double-word fixed-point MRAC technique for the speed controller.
Application of simple adaptive control to water hydraulic servo cylinder system
NASA Astrophysics Data System (ADS)
Ito, Kazuhisa; Yamada, Tsuyoshi; Ikeo, Shigeru; Takahashi, Koji
2012-09-01
Although conventional model reference adaptive control (MRAC) achieves good tracking performance for cylinder control, the controller structure is much more complicated and has less robustness to disturbance in real applications. This paper discusses the use of simple adaptive control (SAC) for positioning a water hydraulic servo cylinder system. Compared with MRAC, SAC has a simpler and lower order structure, i.e., higher feasibility. The control performance of SAC is examined and evaluated on a water hydraulic servo cylinder system. With the recent increased concerns over global environmental problems, the water hydraulic technique using pure tap water as a pressure medium has become a new drive source comparable to electric, oil hydraulic, and pneumatic drive systems. This technique is also preferred because of its high power density, high safety against fire hazards in production plants, and easy availability. However, the main problems for precise control in a water hydraulic system are steady state errors and overshoot due to its large friction torque and considerable leakage flow. MRAC has been already applied to compensate for these effects, and better control performances have been obtained. However, there have been no reports on the application of SAC for water hydraulics. To make clear the merits of SAC, the tracking control performance and robustness are discussed based on experimental results. SAC is confirmed to give better tracking performance compared with PI control, and a control precision comparable to MRAC (within 10 μm of the reference position) and higher robustness to parameter change, despite the simple controller. The research results ensure a wider application of simple adaptive control in real mechanical systems.
H∞ Adaptive tracking control for switched systems based on an average dwell-time method
NASA Astrophysics Data System (ADS)
Wu, Caiyun; Zhao, Jun
2015-10-01
This paper investigates the H∞ state tracking model reference adaptive control (MRAC) problem for a class of switched systems using an average dwell-time method. First, a stability criterion is established for a switched reference model. Then, an adaptive controller is designed and the state tracking control problem is converted into the stability analysis. The global practical stability of the error switched system can be guaranteed under a class of switching signals characterised by an average dwell time. Consequently, sufficient conditions for the solvability of the H∞ state tracking MRAC problem are derived. An example of highly manoeuvrable aircraft technology vehicle is given to demonstrate the feasibility and effectiveness of the proposed design method.
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.
NASA Technical Reports Server (NTRS)
Campbell, Stefan F.; Kaneshige, John T.; Nguyen, Nhan T.; Krishakumar, Kalmanje S.
2010-01-01
Presented here is the evaluation of multiple adaptive control technologies for a generic transport aircraft simulation. For this study, seven model reference adaptive control (MRAC) based technologies were considered. Each technology was integrated into an identical dynamic-inversion control architecture and tuned using a methodology based on metrics and specific design requirements. Simulation tests were then performed to evaluate each technology s sensitivity to time-delay, flight condition, model uncertainty, and artificially induced cross-coupling. The resulting robustness and performance characteristics were used to identify potential strengths, weaknesses, and integration challenges of the individual adaptive control technologies
Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum
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. PMID:26257638
Experimental investigation of adaptive control of a parallel manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Antrazi, Sami S.
1992-01-01
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
NASA Astrophysics Data System (ADS)
Abedini, Mohammad; Nojoumian, Mohammad Ali; Salarieh, Hassan; Meghdari, Ali
2015-08-01
In this paper, model reference control of a fractional order system has been discussed. In order to control the fractional order plant, discrete-time approximation methods have been applied. Plant and reference model are discretized by Grünwald-Letnikov definition of the fractional order derivative using "Short Memory Principle". Unknown parameters of the fractional order system are appeared in the discrete time approximate model as combinations of parameters of the main system. The discrete time MRAC via RLS identification is modified to estimate the parameters and control the fractional order plant. Numerical results show the effectiveness of the proposed method of model reference adaptive control.
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.
Adaptive Control Model Reveals Systematic Feedback and Key Molecules in Metabolic Pathway Regulation
Moffitt, Richard A.; Merrill, Alfred H.; Wang, May D.
2011-01-01
Abstract Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb. PMID:21314456
NASA Technical Reports Server (NTRS)
Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus
2014-01-01
Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.
Adaptive Control for Autonomous Navigation of Mobile Robots Considering Time Delay and Uncertainty
NASA Astrophysics Data System (ADS)
Armah, Stephen Kofi
second-order altitude models for the quadrotor, AR.Drone 2.0. Proportional (P), pole placement or proportional plus velocity (PV), linear quadratic regulator (LQR), and model reference adaptive control (MRAC) controllers are designed and validated through simulations using MATLAB/Simulink. Control input saturation and time delay in the controlled systems are also studied. MATLAB graphical user interface (GUI) and Simulink programs are developed to implement the controllers on the drone. Thirdly, the time delay in the drone's control system is estimated using analytical and experimental methods. In the experimental approach, the transient properties of the experimental altitude responses are compared to those of simulated responses. The analytical approach makes use of the Lambert W function to obtain analytical solutions of scalar first-order delay differential equations (DDEs). A time-delayed P-feedback control system (retarded type) is used in estimating the time delay. Then an improved system performance is obtained by incorporating the estimated time delay in the design of the PV control system (neutral type) and PV-MRAC control system. Furthermore, the stability of a parametric perturbed linear time-invariant (LTI) retarded-type system is studied. This is done by analytically calculating the stability radius of the system. Simulation of the control system is conducted to confirm the stability. This robust control design and uncertainty analysis are conducted for first-order and second-order quadrotor models. Lastly, the robustly designed PV and PV-MRAC control systems are used to autonomously track multiple waypoints. Also, the robustness of the PV-MRAC controller is tested against a baseline PV controller using the payload capability of the drone. It is shown that the PV-MRAC offers several benefits over the fixed-gain approach of the PV controller. The adaptive control is found to offer enhanced robustness to the payload fluctuations.
Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft
NASA Technical Reports Server (NTRS)
Burken, John J.
2007-01-01
The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.
The cost of model reference adaptive control - Analysis, experiments, and optimization
NASA Technical Reports Server (NTRS)
Messer, R. S.; Haftka, R. T.; Cudney, H. H.
1993-01-01
In this paper the performance of Model Reference Adaptive Control (MRAC) is studied in numerical simulations and verified experimentally with the objective of understanding how differences between the plant and the reference model affect the control effort. MRAC is applied analytically and experimentally to a single degree of freedom system and analytically to a MIMO system with controlled differences between the model and the plant. It is shown that the control effort is sensitive to differences between the plant and the reference model. The effects of increased damping in the reference model are considered, and it is shown that requiring the controller to provide increased damping actually decreases the required control effort when differences between the plant and reference model exist. This result is useful because one of the first attempts to counteract the increased control effort due to differences between the plant and reference model might be to require less damping, however, this would actually increase the control effort. Optimization of weighting matrices is shown to help reduce the increase in required control effort. However, it was found that eventually the optimization resulted in a design that required an extremely high sampling rate for successful realization.
Joint-space adaptive control of a 6 DOF end-effector with closed-kinematic chain mechanism
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Zhou, Zhen-Lei
1989-01-01
The development is presented for a joint-space adaptive scheme that controls the joint position of a six-degree-of-freedom (DOF) robot end-effector performing fine and precise motion within a very limited workspace. The end-effector was built to study autonomous assembly of NASA hardware in space. The design of the adaptive controller is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method. In the development, it is assumed that the end-effector performs slowly varying motion. Computer simulation is performed to investigate the performance of the developed control scheme on position control of the end-effector. Simulation results manifest that the adaptive control scheme provides excellent tracking of several test paths.
NASA Astrophysics Data System (ADS)
Chowdhary, Girish; Mühlegg, Maximilian; Johnson, Eric
2014-08-01
In model reference adaptive control (MRAC) the modelling uncertainty is often assumed to be parameterised with time-invariant unknown ideal parameters. The convergence of parameters of the adaptive element to these ideal parameters is beneficial, as it guarantees exponential stability, and makes an online learned model of the system available. Most MRAC methods, however, require persistent excitation of the states to guarantee that the adaptive parameters converge to the ideal values. Enforcing PE may be resource intensive and often infeasible in practice. This paper presents theoretical analysis and illustrative examples of an adaptive control method that leverages the increasing ability to record and process data online by using specifically selected and online recorded data concurrently with instantaneous data for adaptation. It is shown that when the system uncertainty can be modelled as a combination of known nonlinear bases, simultaneous exponential tracking and parameter error convergence can be guaranteed if the system states are exciting over finite intervals such that rich data can be recorded online; PE is not required. Furthermore, the rate of convergence is directly proportional to the minimum singular value of the matrix containing online recorded data. Consequently, an online algorithm to record and forget data is presented and its effects on the resulting switched closed-loop dynamics are analysed. It is also shown that when radial basis function neural networks (NNs) are used as adaptive elements, the method guarantees exponential convergence of the NN parameters to a compact neighbourhood of their ideal values without requiring PE. Flight test results on a fixed-wing unmanned aerial vehicle demonstrate the effectiveness of the method.
Decentralized adaptive control
NASA Technical Reports Server (NTRS)
Oh, B. J.; Jamshidi, M.; Seraji, H.
1988-01-01
A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.
Geometry Modeling and Adaptive Control of Air-Breathing Hypersonic Vehicles
NASA Astrophysics Data System (ADS)
Vick, Tyler Joseph
Air-breathing hypersonic vehicles have the potential to provide global reach and affordable access to space. Recent technological advancements have made scramjet-powered flight achievable, as evidenced by the successes of the X-43A and X-51A flight test programs over the last decade. Air-breathing hypersonic vehicles present unique modeling and control challenges in large part due to the fact that scramjet propulsion systems are highly integrated into the airframe, resulting in strongly coupled and often unstable dynamics. Additionally, the extreme flight conditions and inability to test fully integrated vehicle systems larger than X-51 before flight leads to inherent uncertainty in hypersonic flight. This thesis presents a means to design vehicle geometries, simulate vehicle dynamics, and develop and analyze control systems for hypersonic vehicles. First, a software tool for generating three-dimensional watertight vehicle surface meshes from simple design parameters is developed. These surface meshes are compatible with existing vehicle analysis tools, with which databases of aerodynamic and propulsive forces and moments can be constructed. A six-degree-of-freedom nonlinear dynamics simulation model which incorporates this data is presented. Inner-loop longitudinal and lateral control systems are designed and analyzed utilizing the simulation model. The first is an output feedback proportional-integral linear controller designed using linear quadratic regulator techniques. The second is a model reference adaptive controller (MRAC) which augments this baseline linear controller with an adaptive element. The performance and robustness of each controller are analyzed through simulated time responses to angle-of-attack and bank angle commands, while various uncertainties are introduced. The MRAC architecture enables the controller to adapt in a nonlinear fashion to deviations from the desired response, allowing for improved tracking performance, stability, and
NASA Technical Reports Server (NTRS)
Narendra, K. S.; Annaswamy, A. M.
1985-01-01
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
Adaptive sequential controller
El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso
1994-01-01
An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.
NASA Astrophysics Data System (ADS)
Reif, Konrad
Die adaptive Fahrgeschwindigkeitsregelung (ACC, Adaptive Cruise Control) ist eine Weiterentwicklung der konventionellen Fahrgeschwindigkeitsregelung, die eine konstante Fahrgeschwindigkeit einstellt. ACC überwacht mittels eines Radarsensors den Bereich vor dem Fahrzeug und passt die Geschwindigkeit den Gegebenheiten an. ACC reagiert auf langsamer vorausfahrende oder einscherende Fahrzeuge mit einer Reduzierung der Geschwindigkeit, sodass der vorgeschriebene Mindestabstand zum vorausfahrenden Fahrzeug nicht unterschritten wird. Hierzu greift ACC in Antrieb und Bremse ein. Sobald das vorausfahrende Fahrzeug beschleunigt oder die Spur verlässt, regelt ACC die Geschwindigkeit wieder auf die vorgegebene Sollgeschwindigkeit ein (Bild 1). ACC steht somit für eine Geschwindigkeitsregelung, die sich dem vorausfahrenden Verkehr anpasst.
Adaptive Femtosecond Quantum Control
NASA Astrophysics Data System (ADS)
Gerber, Gustav
2003-03-01
Obtaining active control over the dynamics of quantum-mechanical systems is a fascinating perspective in modern physics. A promising tool for this purpose is available with femtosecond laser technologies. The intrinsically broad spectral distribution and the phase function of femtosecond laser pulses can be specifically manipulated by pulse shapers to drive molecular systems coherently into the desired reaction pathways [1]. The approach of adaptive femtosecond quantum control follows the suggestion of Judson and Rabitz [2], in which a computer-controlled pulse shaper is used in combination with a learning algorithm [3] and direct feedback from the experiment to achieve coherent control over quantum-mechanical processes in an automated fashion, without requiring any model for the system's response. This technique can be applied to the control of gas-phase photodissociation processes [4]. Different bond-cleaving reactions can be preferentially selected, resulting in chemically different products. Prior knowledge about molecular Hamiltonians or reaction mechanisms is not required in this automated control loop, and this scheme works for complex systems. Adaptive pulse-shaping techniques can be transferred to the control of photoprocesses in the liquid phase as well, motivated by the wish to achieve control at particle densities high enough for (bimolecular) synthetic-chemical applications. Chemically selective molecular excitation is achieved by many-parameter adaptive quantum control [5], despite the failure of typical single-parameter approaches (such as wavelength control, intensity control, or linear chirp control). This experiment demonstrates that photoprocesses in two different molecular species can be controlled simultaneously. Applications are envisioned in bimolecular reaction control where specific educt molecules could selectively be "activated" for purposes of chemical synthesis. A new technological development further increases the possibilities and
Adaptive control for accelerators
Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.
1991-01-01
An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.
Adaptive nonlinear flight control
NASA Astrophysics Data System (ADS)
Rysdyk, Rolf Theoduor
1998-08-01
Research under supervision of Dr. Calise and Dr. Prasad at the Georgia Institute of Technology, School of Aerospace Engineering. has demonstrated the applicability of an adaptive controller architecture. The architecture successfully combines model inversion control with adaptive neural network (NN) compensation to cancel the inversion error. The tiltrotor aircraft provides a specifically interesting control design challenge. The tiltrotor aircraft is capable of converting from stable responsive fixed wing flight to unstable sluggish hover in helicopter configuration. It is desirable to provide the pilot with consistency in handling qualities through a conversion from fixed wing flight to hover. The linear model inversion architecture was adapted by providing frequency separation in the command filter and the error-dynamics, while not exiting the actuator modes. This design of the architecture provides for a model following setup with guaranteed performance. This in turn allowed for convenient implementation of guaranteed handling qualities. A rigorous proof of boundedness is presented making use of compact sets and the LaSalle-Yoshizawa theorem. The analysis allows for the addition of the e-modification which guarantees boundedness of the NN weights in the absence of persistent excitation. The controller is demonstrated on the Generic Tiltrotor Simulator of Bell-Textron and NASA Ames R.C. The model inversion implementation is robustified with respect to unmodeled input dynamics, by adding dynamic nonlinear damping. A proof of boundedness of signals in the system is included. The effectiveness of the robustification is also demonstrated on the XV-15 tiltrotor. The SHL Perceptron NN provides a more powerful application, based on the universal approximation property of this type of NN. The SHL NN based architecture is also robustified with the dynamic nonlinear damping. A proof of boundedness extends the SHL NN augmentation with robustness to unmodeled actuator
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.
Output Feedback M-MRAC Backstepping With Aerospace Applications
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje Sriniva
2014-01-01
The paper presents a certainty equivalence output feedback backstepping adaptive control design method for the systems of any relative degree with unmatched uncertainties without over-parametrization. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The approach is applied to aerospace control problems and tested in numerical simulations.
Aircraft adaptive learning control
NASA Technical Reports Server (NTRS)
Lee, P. S. T.; Vanlandingham, H. F.
1979-01-01
The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.
Adaptive Control Of Remote Manipulator
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1989-01-01
Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.
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.
Criticality of Adaptive Control Dynamics
NASA Astrophysics Data System (ADS)
Patzelt, Felix; Pawelzik, Klaus
2011-12-01
We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.
Adaptive Control For Flexible Structures
NASA Technical Reports Server (NTRS)
Bayard, David S.; Ih, Che-Hang Charles; Wang, Shyh Jong
1988-01-01
Paper discusses ways to cope with measurement noise in adaptive control system for large, flexible structure in outer space. System generates control signals for torque and thrust actuators to turn all or parts of structure to desired orientations while suppressing torsional and other vibrations. Main result of paper is general theory for introduction of filters to suppress measurement noise while preserving stability.
An adaptive inverse kinematics algorithm for robot manipulators
NASA Technical Reports Server (NTRS)
Colbaugh, R.; Glass, K.; Seraji, H.
1990-01-01
An adaptive algorithm for solving the inverse kinematics problem for robot manipulators is presented. The algorithm is derived using model reference adaptive control (MRAC) theory and is computationally efficient for online applications. The scheme requires no a priori knowledge of the kinematics of the robot if Cartesian end-effector sensing is available, and it requires knowledge of only the forward kinematics if joint position sensing is used. Computer simulation results are given for the redundant seven-DOF robotics research arm, demonstrating that the proposed algorithm yields accurate joint angle trajectories for a given end-effector position/orientation trajectory.
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.
Adaptable state based control system
NASA Technical Reports Server (NTRS)
Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)
2004-01-01
An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.
Effects of incomplete adaptation and disturbance in adaptive control.
NASA Technical Reports Server (NTRS)
Lindorff, D. P.
1972-01-01
In this paper consideration is given to the effects of disturbance and incomplete parameter adaptation on the performance of adaptive control systems in which Liapunov theory is used in deriving the control law. A design equation for the bounded error is derived. It is further shown that parameters in the adaptive controller may not converge in the presence of disturbance unless the input signal has a rich enough frequency constant. Design examples are presented.
Adaptive Force Control in Compliant Motion
NASA Technical Reports Server (NTRS)
Seraji, H.
1994-01-01
This paper addresses the problem of controlling a manipulator in compliant motion while in contact with an environment having an unknown stiffness. Two classes of solutions are discussed: adaptive admittance control and adaptive compliance control. In both admittance and compliance control schemes, compensator adaptation is used to ensure a stable and uniform system performance.
Keck adaptive optics: control subsystem
Brase, J.M.; An, J.; Avicola, K.
1996-03-08
Adaptive optics on the Keck 10 meter telescope will provide an unprecedented level of capability in high resolution ground based astronomical imaging. The system is designed to provide near diffraction limited imaging performance with Strehl {gt} 0.3 n median Keck seeing of r0 = 25 cm, T =10 msec at 500 nm wavelength. The system will be equipped with a 20 watt sodium laser guide star to provide nearly full sky coverage. The wavefront control subsystem is responsible for wavefront sensing and the control of the tip-tilt and deformable mirrors which actively correct atmospheric turbulence. The spatial sampling interval for the wavefront sensor and deformable mirror is de=0.56 m which gives us 349 actuators and 244 subapertures. This paper summarizes the wavefront control system and discusses particular issues in designing a wavefront controller for the Keck telescope.
Adaptive Controller Effects on Pilot Behavior
NASA Technical Reports Server (NTRS)
Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.
2014-01-01
Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.
Adaptive feedback active noise control
NASA Astrophysics Data System (ADS)
Kuo, Sen M.; Vijayan, Dipa
Feedforward active noise control (ANC) systems use a reference sensor that senses a reference input to the controller. This signal is assumed to be unaffected by the secondary source and is a good measure of the undesired noise to be cancelled by the system. The reference sensor may be acoustic (e.g., microphone) or non-acoustic (e.g., tachometer, optical transducer). An obvious problem when using acoustic sensors is that the reference signal may be corrupted by the canceling signal generated by the secondary source. This problem is known as acoustic feedback. One way of avoiding this is by using a feedback active noise control (FANC) system which dispenses with the reference sensor. The FANC technique originally proposed by Olson and May employs a high gain negative feedback amplifier. This system suffered from the drawback that the error microphone had to be placed very close to the loudspeaker. The operation of the system was restricted to low frequency range and suffered from instability due to the possibility of positive feedback. Feedback systems employing adaptive filtering techniques for active noise control were developed. This paper presents the FANC system modeled as an adaptive prediction scheme.
Adaptive Flight Control for Aircraft Safety Enhancements
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.
2008-01-01
This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.
Engine identification for adaptive control
NASA Technical Reports Server (NTRS)
Leonard, R. G.; Arnett, E. M.
1980-01-01
An attempt to obtain a dynamic model for a turbofan gas turbine engine for the purpose of adaptive control is described. The requirements for adaptive control indicate that a dynamic model should be identified from data sampled during engine operation. The dynamic model identified was of the form of linear differential equations with time varying coefficients. A turbine engine is, however, a highly nonlinear system, so the identified model would be valid only over a small area near the operating point, thus requiring frequent updating of the coefficients in the model. Therefore it is necessary that the identifier use only recent information to perform its function. The identifier selected minimized the square of the equation errors. Known linear systems were used to test the characteristics of the identifier. It was found that the performance was dependent on the number of data points used in the computations and upon the time interval over which the data points were obtained. Preliminary results using an engine deck for the quiet, clean, shorthaul experimental engine indicate that the identified model predicts the engine motion well when there is sufficient dynamic information, that is when the engine is in transient operation.
Dual-arm manipulators with adaptive control
NASA Technical Reports Server (NTRS)
Seraji, Homayoun (Inventor)
1991-01-01
The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.
Simple method for model reference adaptive control
NASA Technical Reports Server (NTRS)
Seraji, H.
1989-01-01
A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.
Statistical Physics for Adaptive Distributed Control
NASA Technical Reports Server (NTRS)
Wolpert, David H.
2005-01-01
A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.
Flexible beam control using an adaptive truss
NASA Technical Reports Server (NTRS)
Warrington, Thomas J.; Horner, C. Garnett
1990-01-01
To demonstrate the feasibility of adaptive trusses for vibration suppression, a 12-ft-long beam is attached to a single cell of an adaptive truss which has three active battens. With the base of the adaptive truss attached to the laboratory frame, the measured strain of the vibrating beam shows the adaptive truss to be very effective in suppressing vibration when subjected to initial conditions. Control is accomplished by a PC/XT computer that implements an LQR-designed control law.
Flight Test 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 validation of adaptive controls has the potential to enhance safety 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.
Adaptive, predictive controller for optimal process control
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Research in digital adaptive flight controllers
NASA Technical Reports Server (NTRS)
Kaufman, H.
1976-01-01
A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Both explicit controllers which directly utilize parameter identification and implicit controllers which do not require identification were considered. Extensive analytical and simulation efforts resulted in the recommendation of two explicit digital adaptive flight controllers. Interface weighted least squares estimation procedures with control logic were developed using either optimal regulator theory or with control logic based upon single stage performance indices.
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.
An adaptive Cartesian control scheme for manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.
Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting
NASA Technical Reports Server (NTRS)
Trujillo, Anna; Gregory, Irene
2013-01-01
Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.
Adaptive control: Myths and realities
NASA Technical Reports Server (NTRS)
Athans, M.; Valavani, L.
1984-01-01
It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.
Adaptive control of dual-arm robots
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
Three strategies for adaptive control of cooperative dual-arm robots are described. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions, while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates.
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.
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.
Adaptive control applied to Space Station attitude control system
NASA Technical Reports Server (NTRS)
Lam, Quang M.; Chipman, Richard; Hu, Tsay-Hsin G.; Holmes, Eric B.; Sunkel, John
1992-01-01
This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.
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.
Adaptive muffler based on controlled flow valves.
Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij
2015-06-01
An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462
Adaptive Impedance Control Of Redundant Manipulators
NASA Technical Reports Server (NTRS)
Seraji, Homayoun; Colbaugh, Richard D.; Glass, Kristin L.
1994-01-01
Improved method of controlling mechanical impedance of end effector of redundant robotic manipulator based on adaptive-control theory. Consists of two subsystems: adaptive impedance controller generating force-control inputs in Cartesian space of end effector to provide desired end-effector-impedance characteristics, and subsystem implementing algorithm that maps force-control inputs into torques applied to joints of manipulator. Accurate control of end effector and effective utilization of redundancy achieved simultaneously by use of method. Potential use to improve performance of such typical impedance-control tasks as deburring edges and accommodating transitions between unconstrained and constrained motions of end effectors.
Adaptive spacecraft attitude control utilizing eigenaxis rotations
NASA Technical Reports Server (NTRS)
Cochran, J. E., Jr.; Colburn, B. K.; Speakman, N. O.
1975-01-01
Conventional and adaptive attitude control of spacecraft which use control moment gyros (CMG's) as torque sources are discussed. Control laws predicated on the assumption of a linear system are used since the spacecraft equations of motion are formulated in an 'eigenaxis system' so that they are essentially linear during 'slow' maneuvers even if large angles are involved. The overall control schemes are 'optimal' in several senses. Eigenaxis rotations and a weighted pseudo-inverse CMG steering law are used and, in the adaptive case, a Model Reference Adaptive System (MRAS) controller based on Liapunov's Second Method is adopted. To substantiate the theory, digital simulation results obtained using physical parameters of a Large Space Telescope type spacecraft are presented. These results indicate that an adaptive control law is often desirable.
Digital adaptive control laws for VTOL aircraft
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.
1979-01-01
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
The adaptive control system of acetylene generator
NASA Astrophysics Data System (ADS)
Kovaliuk, D. O.; Kovaliuk, Oleg; Burlibay, Aron; Gromaszek, Konrad
2015-12-01
The method of acetylene production in acetylene generator was analyzed. It was found that impossible to provide the desired process characteristics by the PID-controller. The adaptive control system of acetylene generator was developed. The proposed system combines the classic controller and fuzzy subsystem for controller parameters tuning.
Adaptive Flight Control Research at NASA
NASA Technical Reports Server (NTRS)
Motter, Mark A.
2008-01-01
A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.
Decentralized digital adaptive control of robot motion
NASA Technical Reports Server (NTRS)
Tarokh, M.
1990-01-01
A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.
On Fractional Model Reference Adaptive Control
Shi, Bao; Dong, Chao
2014-01-01
This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897
On fractional Model Reference Adaptive Control.
Shi, Bao; Yuan, Jian; Dong, Chao
2014-01-01
This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897
Simple adaptive tracking control for mobile robots
NASA Astrophysics Data System (ADS)
Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton
2014-12-01
The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.
An adaptive grid with directional control
NASA Technical Reports Server (NTRS)
Brackbill, J. U.
1993-01-01
An adaptive grid generator for adaptive node movement is here derived by combining a variational formulation of Winslow's (1981) variable-diffusion method with a directional control functional. By applying harmonic-function theory, it becomes possible to define conditions under which there exist unique solutions of the resulting elliptic equations. The results obtained for the grid generator's application to the complex problem posed by the fluid instability-driven magnetic field reconnection demonstrate one-tenth the computational cost of either a Eulerian grid or an adaptive grid without directional control.
Genetic algorithms in adaptive fuzzy control
NASA Technical Reports Server (NTRS)
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
Adaptive Control for Microgravity Vibration Isolation System
NASA Technical Reports Server (NTRS)
Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.
2005-01-01
Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
2008-01-01
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Intelligent Engine Systems: Adaptive Control
NASA Technical Reports Server (NTRS)
Gibson, Nathan
2008-01-01
We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.
Adaptive control of molecular alignment
Horn, C.; Wollenhaupt, M.; Krug, M.; Baumert, T.; Nalda, R. de; Banares, L.
2006-03-15
We demonstrate control on nonadiabatic molecular alignment by using a spectrally phase-shaped laser pulse. An evolutionary algorithm in a closed feedback loop has been used in order to find pulse shapes that maximize a given effect. In particular, this scheme has been applied to the optimization of total alignment, and to the control of the temporal structure of the alignment transient within a revival. Asymmetric temporal pulse shapes have been found to be very effective for the latter and have been studied separately in a single-parameter control scheme. Our experimental results are supported by numerical simulations.
Adaptive Inner-Loop Rover Control
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.
2006-01-01
Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.
Adaptive Control Strategies for Flexible Robotic Arm
NASA Technical Reports Server (NTRS)
Bialasiewicz, Jan T.
1996-01-01
The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.
Language control in bilinguals: The adaptive control hypothesis
Abutalebi, Jubin
2013-01-01
Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013
Language control in bilinguals: The adaptive control hypothesis.
Green, David W; Abutalebi, Jubin
2013-08-01
Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013
Indirect M-MRAC for Systems with Time Varying Parameters and Bounded Disturbances
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje
2012-01-01
The paper presents a prediction-identification model based adaptive control method for uncertain systems with time varying parameters in the presence of bounded external disturbances. The method guarantees desired tracking performance for the system s state and input signals. This is achieved by feeding back the state prediction error to the identification model. It is shown that the desired closed-loop properties are obtained with fast adaptation when the error feedback gain is selected proportional to the square root of the adaptation rate. The theoretical findings are confirmed via a simulation example.
Adaptive gain control during human perceptual choice
Cheadle, Samuel; Wyart, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Castañón, Santiago Herce; Summerfield, Christopher
2015-01-01
Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals, and in cortical responses measured with functional neuroimaging. These data can be accounted for with a new serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence. PMID:24656259
Adaptive output feedback control of flexible systems
NASA Astrophysics Data System (ADS)
Yang, Bong-Jun
Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in
Dual adaptive control: Design principles and applications
NASA Technical Reports Server (NTRS)
Mookerjee, Purusottam
1988-01-01
The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.
Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.
Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad
2016-01-01
In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084
Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV
Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad
2016-01-01
In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084
Adaptive neural control of aeroelastic response
NASA Astrophysics Data System (ADS)
Lichtenwalner, Peter F.; Little, Gerald R.; Scott, Robert C.
1996-05-01
The Adaptive Neural Control of Aeroelastic Response (ANCAR) program is a joint research and development effort conducted by McDonnell Douglas Aerospace (MDA) and the National Aeronautics and Space Administration, Langley Research Center (NASA LaRC) under a Memorandum of Agreement (MOA). The purpose of the MOA is to cooperatively develop the smart structure technologies necessary for alleviating undesirable vibration and aeroelastic response associated with highly flexible structures. Adaptive control can reduce aeroelastic response associated with buffet and atmospheric turbulence, it can increase flutter margins, and it may be able to reduce response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Phase I of the ANCAR program involved development and demonstration of a neural network-based semi-adaptive flutter suppression system which used a neural network for scheduling control laws as a function of Mach number and dynamic pressure. This controller was tested along with a robust fixed-gain control law in NASA's Transonic Dynamics Tunnel (TDT) utilizing the Benchmark Active Controls Testing (BACT) wing. During Phase II, a fully adaptive on-line learning neural network control system has been developed for flutter suppression which will be tested in 1996. This paper presents the results of Phase I testing as well as the development progress of Phase II.
Adaptive neural control of spacecraft using control moment gyros
NASA Astrophysics Data System (ADS)
Leeghim, Henzeh; Kim, Donghoon
2015-03-01
An adaptive control technique is applied to reorient spacecraft with uncertainty using control moment gyros. A nonlinear quaternion feedback law is chosen as a baseline controller. An additional adaptive control input supported by neural networks can estimate and eliminate unknown terms adaptively. The normalized input neural networks are considered for reliable computation of the adaptive input. To prove the stability of the closed-loop dynamics with the control law, the Lyapunov stability theory is considered. Accordingly, the proposed approach results in the uniform ultimate boundedness in tracking error. For reorientation maneuvers, control moment gyros are utilized with a well-known singularity problem described in this work investigated by predicting one-step ahead singularity index. A momentum vector recovery approach using magnetic torquers is also introduced to evaluate the avoidance strategies indirectly. Finally, the suggested methods are demonstrated by numerical simulation studies.
Neuronal Control of Adaptive Thermogenesis
Yang, Xiaoyong; Ruan, Hai-Bin
2015-01-01
The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT), dysfunction of which lies at the core of obesity and associated metabolic disorders. By contrast, brown adipose tissue (BAT) burns fat and dissipates chemical energy as heat. The development and activation of “brown-like” adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation. PMID:26441839
Hybrid adaptive control of a dragonfly model
NASA Astrophysics Data System (ADS)
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
2012-02-01
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
Robust, Practical Adaptive Control for Launch Vehicles
NASA Technical Reports Server (NTRS)
Orr, Jeb. S.; VanZwieten, Tannen S.
2012-01-01
A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.
Evolving Systems and Adaptive Key Component Control
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Balas, Mark J.
2009-01-01
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.
Adaptive control of a robotic manipulator
NASA Technical Reports Server (NTRS)
Lewis, R. A.
1977-01-01
A control hierarchy for a robotic manipulator is described. The hierarchy includes perception and robot/environment interaction, the latter consisting of planning, path control, and terminal guidance loops. Environment-sensitive features include the provision of control governed by proximity, tactile, and visual sensors as well as the usual kinematic sensors. The manipulator is considered as part of an overall robot system. 'Adaptive control' in the present context refers to both the hierarchical nature of the control system and to its environment-responsive nature.
Adaptive control of sulfur recovery units
Cunningham, D.B. )
1994-08-01
In a recent trial, adaptive control reduce the standard deviation of the tail gas ratio by 38%--increasing sulfur recovery efficiency by an estimated 0.3%. By using the controller on other control loops in the process, further increases are expected. Improved process control is a cost effective way to meet existing emissions limits. Future legislation will reduce the permissible emissions level, so it is imperative that existing sulfur recovery equipment by operated at peak efficiency. Peak efficiency can only be achieved with good trim air control, since it determines recovery efficiency. But process time delays and changes in the incoming gas stream make good control difficult to achieve. An adaptive controller is well suited to trim air control, since it can easily handle time delay sand adapt to changing process conditions. The improved efficiency is a considerable economic benefit to gas processing plants, since: (1) capital and operating expenses needed to improve recovery efficiency are avoided; (2) increased production is possible, since sulfur license limits are easier to meet; and (3) catalyst bed life is extended. Results of the test are 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.
Predictive Control of Speededness in Adaptive Testing
ERIC Educational Resources Information Center
van der Linden, Wim J.
2009-01-01
An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…
Adaptive control system for gas producing wells
Fedor, Pashchenko; Sergey, Gulyaev; Alexander, Pashchenko
2015-03-10
Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation.
Robust Adaptive Control In Hilbert Space
NASA Technical Reports Server (NTRS)
Wen, John Ting-Yung; Balas, Mark J.
1990-01-01
Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.
Robust adaptive control of HVDC systems
Reeve, J.; Sultan, M. )
1994-07-01
The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.
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.
Modeling and adaptive control of acoustic noise
NASA Astrophysics Data System (ADS)
Venugopal, Ravinder
Active noise control is a problem that receives significant attention in many areas including aerospace and manufacturing. The advent of inexpensive high performance processors has made it possible to implement real-time control algorithms to effect active noise control. Both fixed-gain and adaptive methods may be used to design controllers for this problem. For fixed-gain methods, it is necessary to obtain a mathematical model of the system to design controllers. In addition, models help us gain phenomenological insights into the dynamics of the system. Models are also necessary to perform numerical simulations. However, models are often inadequate for the purpose of controller design because they involve parameters that are difficult to determine and also because there are always unmodeled effects. This fact motivates the use of adaptive algorithms for control since adaptive methods usually require significantly less model information than fixed-gain methods. The first part of this dissertation deals with derivation of a state space model of a one-dimensional acoustic duct. Two types of actuation, namely, a side-mounted speaker (interior control) and an end-mounted speaker (boundary control) are considered. The techniques used to derive the model of the acoustic duct are extended to the problem of fluid surface wave control. A state space model of small amplitude surfaces waves of a fluid in a rectangular container is derived and two types of control methods, namely, surface pressure control and map actuator based control are proposed and analyzed. The second part of this dissertation deals with the development of an adaptive disturbance rejection algorithm that is applied to the problem of active noise control. ARMARKOV models which have the same structure as predictor models are used for system representation. The algorithm requires knowledge of only one path of the system, from control to performance, and does not require a measurement of the disturbance nor
Geometry control in prestressed adaptive space trusses
NASA Technical Reports Server (NTRS)
Sener, Murat; Utku, Senol; Wada, Ben K.
1993-01-01
In this work the actuator placement problem for the precision control in prestressed adaptive space trusses is studied. These structures cannot be statically determinate, implying that the length-adjusting actuators have to work against the existing prestressing forces, and also against the stresses caused by the actuation. This type of difficulties does not exist in statically determinate adaptive trusses where, except for overcoming the friction, the actuators operate under zero axial force, and require almost no energy. The actuator placement problem in statically inderterminate trusses is, therefore, governed seriously by the energy and the strength requirements. The paper provides various methodologies for the actuator placement problem in prestressed space trusses.
Adaptive control of Space Station with control moment gyros
NASA Technical Reports Server (NTRS)
Bishop, Robert H.; Paynter, Scott J.; Sunkel, John W.
1992-01-01
An adaptive approach to Space Station attitude control is investigated. The main components of the controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is a full-state feedback space station baseline control law. The control gain calculation is based on linear-quadratic regulator theory with eigenvalues placement in a vertical strip. The parameter identification scheme is a recursive extended Kalman filter that estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to estimate Space Station inertias accurately during nominal control moment gyro operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.
Adaptive control strategies for flexible robotic arm
NASA Technical Reports Server (NTRS)
Bialasiewicz, Jan T.
1993-01-01
The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.
An adaptive learning control system for aircraft
NASA Technical Reports Server (NTRS)
Mekel, R.; Nachmias, S.
1976-01-01
A learning control system is developed which blends the gain scheduling and adaptive control into a single learning system that has the advantages of both. An important feature of the developed learning control system is its capability to adjust the gain schedule in a prescribed manner to account for changing aircraft operating characteristics. Furthermore, if tests performed by the criteria of the learning system preclude any possible change in the gain schedule, then the overall system becomes an ordinary gain scheduling system. Examples are discussed.
Adaptive spark control with knock detection
Boccadoro, V.; Kizer, T.
1984-01-01
Since 1981 RENIX has produced for RENAULT a digital ignition system with knock detection and advance correction capabilities. The knock detection uses the signal from a wide bank accelerometre mounted on the cylinder head. Good signal to noise ratio is obtained primarily through angular discrimination. RENIX's module technology leads to high performance to cost radio. The anti knock capability has now been included in RENAULT's latest engine control system to appear in the USA on MY 85. The presence of a powerful microprocessor allowed the development of an advanced control strategy which includes individual cylinder corrections and adaptive control. This is described together with the vehicle application at AMC.
Parallel computations and control of adaptive structures
NASA Technical Reports Server (NTRS)
Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)
1991-01-01
The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.
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.
F-8C adaptive flight control laws
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Harvey, C. A.; Stein, G.; Carlson, D. N.; Hendrick, R. C.
1977-01-01
Three candidate digital adaptive control laws were designed for NASA's F-8C digital flyby wire aircraft. Each design used the same control laws but adjusted the gains with a different adaptative algorithm. The three adaptive concepts were: high-gain limit cycle, Liapunov-stable model tracking, and maximum likelihood estimation. Sensors were restricted to conventional inertial instruments (rate gyros and accelerometers) without use of air-data measurements. Performance, growth potential, and computer requirements were used as criteria for selecting the most promising of these candidates for further refinement. The maximum likelihood concept was selected primarily because it offers the greatest potential for identifying several aircraft parameters and hence for improved control performance in future aircraft application. In terms of identification and gain adjustment accuracy, the MLE design is slightly superior to the other two, but this has no significant effects on the control performance achievable with the F-8C aircraft. The maximum likelihood design is recommended for flight test, and several refinements to that design are proposed.
Geometric view of adaptive optics control.
Wiberg, Donald M; Max, Claire E; Gavel, Donald T
2005-05-01
The objective of an astronomical adaptive optics control system is to minimize the residual wave-front error remaining on the science-object wave fronts after being compensated for atmospheric turbulence and telescope aberrations. Minimizing the mean square wave-front residual maximizes the Strehl ratio and the encircled energy in pointlike images and maximizes the contrast and resolution of extended images. We prove the separation principle of optimal control for application to adaptive optics so as to minimize the mean square wave-front residual. This shows that the residual wave-front error attributable to the control system can be decomposed into three independent terms that can be treated separately in design. The first term depends on the geometry of the wave-front sensor(s), the second term depends on the geometry of the deformable mirror(s), and the third term is a stochastic term that depends on the signal-to-noise ratio. The geometric view comes from understanding that the underlying quantity of interest, the wave-front phase surface, is really an infinite-dimensional vector within a Hilbert space and that this vector space is projected into subspaces we can control and measure by the deformable mirrors and wave-front sensors, respectively. When the control and estimation algorithms are optimal, the residual wave front is in a subspace that is the union of subspaces orthogonal to both of these projections. The method is general in that it applies both to conventional (on-axis, ground-layer conjugate) adaptive optics architectures and to more complicated multi-guide-star- and multiconjugate-layer architectures envisaged for future giant telescopes. We illustrate the approach by using a simple example that has been worked out previously [J. Opt. Soc. Am. A 73, 1171 (1983)] for a single-conjugate, static atmosphere case and follow up with a discussion of how it is extendable to general adaptive optics architectures. PMID:15898546
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Durham adaptive optics real-time controller.
Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy
2010-11-10
The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems. PMID:21068868
Applying statistical process control to the adaptive rate control problem
NASA Astrophysics Data System (ADS)
Manohar, Nelson R.; Willebeek-LeMair, Marc H.; Prakash, Atul
1997-12-01
Due to the heterogeneity and shared resource nature of today's computer network environments, the end-to-end delivery of multimedia requires adaptive mechanisms to be effective. We present a framework for the adaptive streaming of heterogeneous media. We introduce the application of online statistical process control (SPC) to the problem of dynamic rate control. In SPC, the goal is to establish (and preserve) a state of statistical quality control (i.e., controlled variability around a target mean) over a process. We consider the end-to-end streaming of multimedia content over the internet as the process to be controlled. First, at each client, we measure process performance and apply statistical quality control (SQC) with respect to application-level requirements. Then, we guide an adaptive rate control (ARC) problem at the server based on the statistical significance of trends and departures on these measurements. We show this scheme facilitates handling of heterogeneous media. Last, because SPC is designed to monitor long-term process performance, we show that our online SPC scheme could be used to adapt to various degrees of long-term (network) variability (i.e., statistically significant process shifts as opposed to short-term random fluctuations). We develop several examples and analyze its statistical behavior and guarantees.
Genetic Adaptive Control for PZT Actuators
NASA Technical Reports Server (NTRS)
Kim, Jeongwook; Stover, Shelley K.; Madisetti, Vijay K.
1995-01-01
A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.
Direct adaptive control for nonlinear uncertain dynamical systems
NASA Astrophysics Data System (ADS)
Hayakawa, Tomohisa
In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances
Neural Control Adaptation to Motor Noise Manipulation
Hasson, Christopher J.; Gelina, Olga; Woo, Garrett
2016-01-01
Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487
Neural Control Adaptation to Motor Noise Manipulation.
Hasson, Christopher J; Gelina, Olga; Woo, Garrett
2016-01-01
Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487
Comments on 'Hamiltonian adaptive control of spacecraft'
NASA Astrophysics Data System (ADS)
Fossen, Thor I.
1993-04-01
In the adaptive scheme presented by Slotine and Benedetto (1990) for attitude tracking control of rigid spacecraft, the spacecraft is parameterized in terms of the inertial frame. This note shows how a parameterization in body coordinates considerably simplifies the representation of the adaptation scheme. The new symbolic expression for the regressor matrix is easy to find even for 6-degrees of freedom (DOF) Hamiltonian systems with a large number of unknown parameters. If the symbolic expression for the regressor matrix is known in advance, the computational complexity is approximately equal for both representations. In the scheme presented by Slotine and Benedetto this is not trivial because the transformation matrix between the inertial frame and the body coordinates is included in the expression for the regressor matrix. Hence, implementation for higher DOF systems is strongly complicated. An example illustrates the advantage of the new representation when modeling a simple three-DOF model of the lateral motion of a space shuttle.
Robust adaptive control for Unmanned Aerial Vehicles
NASA Astrophysics Data System (ADS)
Kahveci, Nazli E.
The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with
Road map to adaptive optimal control. [jet engine control
NASA Technical Reports Server (NTRS)
Boyer, R.
1980-01-01
A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.
Adaptive control of a Stewart platform-based manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.
1993-01-01
A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
A Methodology for Investigating Adaptive Postural Control
NASA Technical Reports Server (NTRS)
McDonald, P. V.; Riccio, G. E.
1999-01-01
Our research on postural control and human-environment interactions provides an appropriate scientific foundation for understanding the skill of mass handling by astronauts in weightless conditions (e.g., extravehicular activity or EVA). We conducted an investigation of such skills in NASA's principal mass-handling simulator, the Precision Air-Bearing Floor, at the Johnson Space Center. We have studied skilled movement-body within a multidisciplinary context that draws on concepts and methods from biological and behavioral sciences (e.g., psychology, kinesiology and neurophysiology) as well as bioengineering. Our multidisciplinary research has led to the development of measures, for manual interactions between individuals and the substantial environment, that plausibly are observable by human sensory systems. We consider these methods to be the most important general contribution of our EVA investigation. We describe our perspective as control theoretic because it draws more on fundamental concepts about control systems in engineering than it does on working constructs from the subdisciplines of biomechanics and motor control in the bio-behavioral sciences. At the same time, we have attempted to identify the theoretical underpinnings of control-systems engineering that are most relevant to control by human beings. We believe that these underpinnings are implicit in the assumptions that cut across diverse methods in control-systems engineering, especially the various methods associated with "nonlinear control", "fuzzy control," and "adaptive control" in engineering. Our methods are based on these theoretical foundations rather than on the mathematical formalisms that are associated with particular methods in control-systems engineering. The most important aspects of the human-environment interaction in our investigation of mass handling are the functional consequences that body configuration and stability have for the pick up of information or the achievement of
Adaptive Accommodation Control Method for Complex Assembly
NASA Astrophysics Data System (ADS)
Kang, Sungchul; Kim, Munsang; Park, Shinsuk
Robotic systems have been used to automate assembly tasks in manufacturing and in teleoperation. Conventional robotic systems, however, have been ineffective in controlling contact force in multiple contact states of complex assemblythat involves interactions between complex-shaped parts. Unlike robots, humans excel at complex assembly tasks by utilizing their intrinsic impedance, forces and torque sensation, and tactile contact clues. By examining the human behavior in assembling complex parts, this study proposes a novel geometry-independent control method for robotic assembly using adaptive accommodation (or damping) algorithm. Two important conditions for complex assembly, target approachability and bounded contact force, can be met by the proposed control scheme. It generates target approachable motion that leads the object to move closer to a desired target position, while contact force is kept under a predetermined value. Experimental results from complex assembly tests have confirmed the feasibility and applicability of the proposed method.
Adaptive control of space based robot manipulators
NASA Technical Reports Server (NTRS)
Walker, Michael W.; Wee, Liang-Boon
1991-01-01
For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.
Adaptive control: Stability, convergence, and robustness
NASA Technical Reports Server (NTRS)
Sastry, Shankar; Bodson, Marc
1989-01-01
The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.
Adaptive method with intercessory feedback control for an intelligent agent
Goldsmith, Steven Y.
2004-06-22
An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.
Adaptive Control Using Residual Mode Filters Applied to Wind Turbines
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Balas, Mark J.
2011-01-01
Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.; Lawrence, D. A.
1981-01-01
The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is provided.
Adaptive Control of Flexible Structures Using Residual Mode Filters
NASA Technical Reports Server (NTRS)
Balas, Mark J.; Frost, Susan
2010-01-01
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.
Adaptive collaborative control of highly redundant robots
NASA Astrophysics Data System (ADS)
Handelman, David A.
2008-04-01
The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.
Wavefront Control for Extreme Adaptive Optics
Poyneer, L A
2003-07-16
Current plans for Extreme Adaptive Optics systems place challenging requirements on wave-front control. This paper focuses on control system dynamics, wave-front sensing and wave-front correction device characteristics. It may be necessary to run an ExAO system after a slower, low-order AO system. Running two independent systems can result in very good temporal performance, provided specific design constraints are followed. The spatially-filtered wave-front sensor, which prevents aliasing and improves PSF sensitivity, is summarized. Different models of continuous and segmented deformable mirrors are studied. In a noise-free case, a piston-tip-tilt segmented MEMS device can achieve nearly equivalent performance to a continuous-sheet DM in compensating for a static phase aberration with use of spatial filtering.
Real-time Adaptive Control Using Neural Generalized Predictive Control
NASA Technical Reports Server (NTRS)
Haley, Pam; Soloway, Don; Gold, Brian
1999-01-01
The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.
Adaptive powertrain control for plugin hybrid electric vehicles
Kedar-Dongarkar, Gurunath; Weslati, Feisel
2013-10-15
A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.
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.
An adaptive control system for wing TE shape control
NASA Astrophysics Data System (ADS)
Dimino, I.; Concilio, A.; Schueller, M.; Gratias, A.
2013-03-01
A key technology to enable morphing aircraft for enhanced aerodynamic performance is the design of an adaptive control system able to emulate target structural shapes. This paper presents an approach to control the shape of a morphing wing by employing internal, integrated actuators acting on the trailing edge. The adaptive-wing concept employs active ribs, driven by servo actuators, controlled in turn by a dedicated algorithm aimed at shaping the wing cross section, according to a pre-defined geometry. The morphing control platform is presented and a suitable control algorithm is implemented in a dedicated routine for real-time simulations. The work is organized as follows. A finite element model of the uncontrolled, non-actuated structure is used to obtain the plant model for actuator torque and displacement control. After having characterized and simulated pure rotary actuator behavior over the structure, selected target wing shapes corresponding to rigid trailing edge rotations are achieved through both open-loop and closed-loop control logics.
Robust adaptive vibration control of a flexible structure.
Khoshnood, A M; Moradi, H M
2014-07-01
Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system. PMID:24703188
Direct adaptive control of manipulators in Cartesian space
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.
Integrated flight/propulsion control - Adaptive engine control system mode
NASA Technical Reports Server (NTRS)
Yonke, W. A.; Terrell, L. A.; Meyers, L. P.
1985-01-01
The adaptive engine control system mode (ADECS) which is developed and tested on an F-15 aircraft with PW1128 engines, using the NASA sponsored highly integrated digital electronic control program, is examined. The operation of the ADECS mode, as well as the basic control logic, the avionic architecture, and the airframe/engine interface are described. By increasing engine pressure ratio (EPR) additional thrust is obtained at intermediate power and above. To modulate the amount of EPR uptrim and to prevent engine stall, information from the flight control system is used. The performance benefits, anticipated from control integration are shown for a range of flight conditions and power settings. It is found that at higher altitudes, the ADECS mode can increase thrust as much as 12 percent, which is used for improved acceleration, improved turn rate, or sustained turn angle.
A survey of adaptive control technology in robotics
NASA Technical Reports Server (NTRS)
Tosunoglu, S.; Tesar, D.
1987-01-01
Previous work on the adaptive control of robotic systems is reviewed. Although the field is relatively new and does not yet represent a mature discipline, considerable attention has been given to the design of sophisticated robot controllers. Here, adaptive control methods are divided into model reference adaptive systems and self-tuning regulators with further definition of various approaches given in each class. The similarity and distinct features of the designed controllers are delineated and tabulated to enhance comparative review.
Full-Scale Flight Research Testbeds: Adaptive and Intelligent Control
NASA Technical Reports Server (NTRS)
Pahle, Joe W.
2008-01-01
This viewgraph presentation describes the adaptive and intelligent control methods used for aircraft survival. The contents include: 1) Motivation for Adaptive Control; 2) Integrated Resilient Aircraft Control Project; 3) Full-scale Flight Assets in Use for IRAC; 4) NASA NF-15B Tail Number 837; 5) Gen II Direct Adaptive Control Architecture; 6) Limited Authority System; and 7) 837 Flight Experiments. A simulated destabilization failure analysis along with experience and lessons learned are also presented.
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.
Modular and Adaptive Control of Sound Processing
NASA Astrophysics Data System (ADS)
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
Least-Squares Adaptive Control Using Chebyshev Orthogonal Polynomials
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Burken, John; Ishihara, Abraham
2011-01-01
This paper presents a new adaptive control approach using Chebyshev orthogonal polynomials as basis functions in a least-squares functional approximation. The use of orthogonal basis functions improves the function approximation significantly and enables better convergence of parameter estimates. Flight control simulations demonstrate the effectiveness of the proposed adaptive control approach.
Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems
Williams, Rube B.
2004-02-04
Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.
Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems
NASA Astrophysics Data System (ADS)
Williams, Rube B.
2004-02-01
Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.
Neural control of chronic stress adaptation
Herman, James P.
2013-01-01
Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process. PMID:23964212
Synthetic consciousness: the distributed adaptive control perspective.
Verschure, Paul F M J
2016-08-19
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID
Adaptive control system for large annular momentum control device
NASA Technical Reports Server (NTRS)
Montgomery, R. C.; Johnson, C. R., Jr.
1981-01-01
A dual momentum vector control concept, consisting of two counterrotating rings (each designated as an annular momentum control device), was studied for pointing and slewing control of large spacecraft. In a disturbance free space environment, the concept provides for three axis pointing and slewing capabilities while requiring no expendables. The approach utilizes two large diameter counterrotating rings or wheels suspended magnetically in many race supports distributed around the antenna structure. When the magnets are energized, attracting the two wheels, the resulting gyroscopic torque produces a rate along the appropriate axis. Roll control is provided by alternating the radiative rotational velocity of the two wheels. Wheels with diameters of 500 to 800 m and with sufficient momentum storage capability require rims only a few centimeters thick. The wheels are extremely flexible; therefore, it is necessary to account for the distributed nature of the rings in the design of the bearing controllers. Also, ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. An adaptive control system designed to handle these problems is described.
Adaptive Force Control For Compliant Motion Of A Robot
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1995-01-01
Two adaptive control schemes offer robust solutions to problem of stable control of forces of contact between robotic manipulator and objects in its environment. They are called "adaptive admittance control" and "adaptive compliance control." Both schemes involve use of force-and torque sensors that indicate contact forces. These schemes performed well when tested in computational simulations in which they were used to control seven-degree-of-freedom robot arm in executing contact tasks. Choice between admittance or compliance control is dictated by requirements of the application at hand.
An adaptive controller for enhancing operator performance during teleoperation
NASA Technical Reports Server (NTRS)
Carignan, Craig R.; Tarrant, Janice M.; Mosier, Gary E.
1989-01-01
An adaptive controller is developed for adjusting robot arm parameters while manipulating payloads of unknown mass and inertia. The controller is tested experimentally in a master/slave configuration where the adaptive slave arm is commanded via human operator inputs from a master. Kinematically similar six-joint master and slave arms are used with the last three joints locked for simplification. After a brief initial adaptation period for the unloaded arm, the slave arm retrieves different size payloads and maneuvers them about the workspace. Comparisons are then drawn with similar tasks where the adaptation is turned off. Several simplifications of the controller dynamics are also addressed and experimentally verified.
Pulse front control with adaptive optics
NASA Astrophysics Data System (ADS)
Sun, B.; Salter, P. S.; Booth, M. J.
2016-03-01
The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.
Adaptive robust control of the EBR-II reactor
Power, M.A.; Edwards, R.M.
1996-05-01
Simulation results are presented for an adaptive H{sub {infinity}} controller, a fixed H{sub {infinity}} controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H{sub {infinity}} controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H{sub {infinity}} and classical controllers. This makes for a superior and more robust controller.
Monitoring the Performance of a Neuro-Adaptive Controller
NASA Technical Reports Server (NTRS)
Schumann, Johann; Gupta, Pramod
2004-01-01
Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.
An adaptive control scheme for coordinated multimanipulator systems
Jonghann Jean; Lichen Fu . Dept. of Electrical Engineering)
1993-04-01
The problem of adaptive coordinated control of multiple robot arms transporting an object is addressed. A stable adaptive control scheme for both trajectory tracking and internal force control is presented. Detailed analyses on tracking properties of the object position, velocity and the internal forces exerted on the object are given. It is shown that this control scheme can achieve satisfactory tracking performance without using the measurement of contact forces and their derivatives. It can be shown that this scheme can be realized by decentralized implementation to reduce the computational burden. Moreover, some efficient adaptive control strategies can be incorporated to reduce the computational complexity.
Adaptive controller for a needle free jet-injector system.
Modak, Ashin; Hogan, N Catherine; Hunter, Ian W
2015-08-01
A nonlinear, sliding mode adaptive controller was created for a needle-free jet injection system. The controller was based on a simplified lumped-sum parameter model of the jet-injection mechanics. The adaptive control scheme was compared to a currently-used Feed-forward+PID controller in both ejection of water into air, and injection of dye into ex-vivo porcine tissue. The adaptive controller was more successful in trajectory tracking and was more robust to the biological variations caused by a tissue load. PMID:26737988
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.
Sense of Control and Career Adaptability among Undergraduate Students
ERIC Educational Resources Information Center
Duffy, Ryan D.
2010-01-01
The current study examined the direct relation of sense of control to career adaptability, as well as its ability to function as a mediator for other established predictors, with a sample of 1,991 undergraduate students. Students endorsing a greater sense of personal control were more likely to view themselves as adaptable to the world of work.…
Closing the Certification Gaps in Adaptive Flight Control Software
NASA Technical Reports Server (NTRS)
Jacklin, Stephen A.
2008-01-01
Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.
Adaptive sliding mode control for a class of chaotic systems
Farid, R.; Ibrahim, A.; Zalam, B.
2015-03-30
Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.
Systems and Methods for Derivative-Free Adaptive Control
NASA Technical Reports Server (NTRS)
Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)
2015-01-01
An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.
Internal Models in Sensorimotor Integration: Perspectives from Adaptive Control Theory
Tin, Chung; Poon, Chi-Sang
2007-01-01
Internal model and adaptive control are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning are reviewed and their possible relevance to motor control is discussed. Possible applicability of Luenberger observer and extended Kalman filter to state estimation problems such as sensorimotor prediction or the resolution of vestibular sensory ambiguity is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal model in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future. PMID:16135881
An averaging analysis of discrete-time indirect adaptive control
NASA Technical Reports Server (NTRS)
Phillips, Stephen M.; Kosut, Robert L.; Franklin, Gene F.
1988-01-01
An averaging analysis of indirect, discrete-time, adaptive control systems is presented. The analysis results in a signal-dependent stability condition and accounts for unmodeled plant dynamics as well as exogenous disturbances. This analysis is applied to two discrete-time adaptive algorithms: an unnormalized gradient algorithm and a recursive least-squares (RLS) algorithm with resetting. Since linearization and averaging are used for the gradient analysis, a local stability result valid for small adaptation gains is found. For RLS with resetting, the assumption is that there is a long time between resets. The results for the two algorithms are virtually identical, emphasizing their similarities in adaptive control.
Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.
Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong
2015-09-01
In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes. PMID:26169122
Adaptive torque control of variable speed wind turbines
NASA Astrophysics Data System (ADS)
Johnson, Kathryn E.
Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.
Hormesis and adaptive cellular control systems
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
Adaptive Fuzzy Control of a Direct Drive Motor
NASA Technical Reports Server (NTRS)
Medina, E.; Kim, Y. T.; Akbaradeh-T., M. -R.
1997-01-01
This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is verified by simulation results.
Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects
NASA Technical Reports Server (NTRS)
Medina, E.; Akbarzadeh-T, M.-R.; Kim, Y. T.
1998-01-01
This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.
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.
Design of Low Complexity Model Reference Adaptive Controllers
NASA Technical Reports Server (NTRS)
Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan
2012-01-01
Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.
Adaptive Instability Suppression Controls in a Liquid-fueled Combustor
NASA Technical Reports Server (NTRS)
Kopasakis, George; DeLaat, John C.
2002-01-01
An adaptive control algorithm has been developed for the suppression of combustion thermo-acoustic instabilities. This technique involves modulating the fuel flow in the combustor with a control phase that continuously slides within the stable phase region, in a back and forth motion. The control method is referred to as Adaptive Sliding Phasor Averaged Control (ASPAC). The control method is evaluated against a simplified simulation of the combustion instability. Plans are to validate the control approach against a more physics-based model and an actual experimental combustor rig.
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
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. PMID:24996074
Smart Rehabilitation Devices: Part II – Adaptive Motion Control
Dong, Shufang; Lu, Ke-Qian; Sun, J. Q.; Rudolph, Katherine
2008-01-01
This article presents a study of adaptive motion control of smart versatile rehabilitation devices using MR fluids. The device provides both isometric and isokinetic strength training and is reconfigurable for several human joints. Adaptive controls are developed to regulate resistance force based on the prescription of the therapist. Special consideration has been given to the human–machine interaction in the adaptive control that can modify the behavior of the device to account for strength gains or muscle fatigue of the human subject. PMID:18548131
Development of a digital adaptive optimal linear regulator flight controller
NASA Technical Reports Server (NTRS)
Berry, P.; Kaufman, H.
1975-01-01
Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.
Discrete-time adaptive control of robot manipulators
NASA Technical Reports Server (NTRS)
Tarokh, M.
1989-01-01
A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.
Disturbance Accommodating Adaptive Control with Application to Wind Turbines
NASA Technical Reports Server (NTRS)
Frost, Susan
2012-01-01
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Identification and dual adaptive control of a turbojet engine
NASA Technical Reports Server (NTRS)
Merrill, W.; Leininger, G.
1979-01-01
The objective of this paper is to utilize the design methods of modern control theory to realize a dual-adaptive feedback control unit for a highly nonlinear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the nonlinear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a dual-adaptive control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.
Adaptive optimization and control using neural networks
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft
NASA Technical Reports Server (NTRS)
Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal
2006-01-01
This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.
Adaptive control of mobile robots using a neural network.
de Sousa Júnior, C; Hermerly, E M
2001-06-01
A Neural Network - based control approach for mobile robot is proposed. The weight adaptation is made on-line, without previous learning. Several possible situations in robot navigation are considered, including uncertainties in the model and presence of disturbance. Weight adaptation laws are presented as well as simulation results. PMID:11574958
Stability and Performance Metrics for Adaptive Flight Control
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens
2009-01-01
This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.
L1 adaptive output-feedback control architectures
NASA Astrophysics Data System (ADS)
Kharisov, Evgeny
This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Adaptive control in series load PWM induction heating inverters
NASA Astrophysics Data System (ADS)
Szelitzky, Tibor; Henrietta Dulf, Eva
2013-12-01
Permanent variations of the electric properties of the load in induction heating equipment make difficult to control the plant. To overcome these disadvantages, the authors propose a new approach based on adaptive control methods. For real plants it is enough to present desired performances or start-up variables for the controller, from which the algorithms tune the controllers by itself. To present the advantages of the proposed controllers, comparisons are made to a PI controller tuned through Ziegler-Nichols method.
Missile guidance law design using adaptive cerebellar model articulation controller.
Lin, Chih-Min; Peng, Ya-Fu
2005-05-01
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments
Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916
Novel hybrid adaptive controller for manipulation in complex perturbation environments.
Smith, Alex M C; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916
Adult Development, Control, and Adaptive Functioning.
ERIC Educational Resources Information Center
Schulz, Richard; And Others
1991-01-01
Research suggests that primary control increases as humans develop from infancy through middle age and then decreases in old age. To minimize losses, individuals rely on cognitively based secondary control processes in middle and old age. Literature on adult control processes is reviewed. (SLD)
Adaptive Importance Sampling for Control and Inference
NASA Astrophysics Data System (ADS)
Kappen, H. J.; Ruiz, H. C.
2016-03-01
Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.
Adaptive hybrid position/force control of robotic manipulators
NASA Technical Reports Server (NTRS)
Pourboghrat, F.
1987-01-01
The problem of position and force control for the compliant motion of the manipulators is considered. The external force and the position of the end-effector are related by a second order impedance function. The force control problem is then translated into a position control problem. For that, an adaptive controller is designed to achieve the compliant motion. The design uses the Liapunov's direct method to derive the adaptation law. The stability of the process is guaranteed from the Liapunov's stability theory. The controller does not require the knowledge of the system parameters for the implementation, and hence is easy for applications.
Digital adaptive controllers for VTOL vehicles. Volume 1: Concept evaluation
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.; Pratt, S. G.
1979-01-01
A digital self-adaptive flight control system was developed for flight test in the VTOL approach and landing technology (VALT) research aircraft (a modified CH-47 helicopter). The control laws accept commands from an automatic on-board guidance system. The primary objective of the control laws is to provide good command-following with a minimum cross-axis response. Three attitudes and vertical velocity are separately commanded. Adaptation of the control laws is based on information from rate and attitude gyros and a vertical velocity measurement. The final design resulted from a comparison of two different adaptive concepts--one based on explicit parameter estimates from a real-time maximum-likelihood estimation algorithm, the other based on an implicit model reference adaptive system. The two designs were compared on the basis of performance and complexity.
Actuator placement in prestressed adaptive trusses for vibration control
NASA Technical Reports Server (NTRS)
Jalihal, P.; Utku, Senol; Wada, Ben K.
1993-01-01
This paper describes the optimal location selection of actuators for vibration control in prestressed adaptive trusses. Since prestressed adaptive trusses are statically indeterminate, the actuators to be used for vibration control purposes must work against (1) existing static axial prestressing forces, (2) static axial forces caused by the actuation, and (3) dynamic axial forces caused by the motion of the mass. In statically determinate adaptive trusses (1) and (2) are non - existing. The actuator placement problem in statically indeterminate trusses is therefore governed by the actuation energy and the actuator strength requirements. Assuming output feedback type control of selected vibration modes in autonomous systems, a procedure is given for the placement of vibration controlling actuators in prestressed adaptive trusses.
Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.
Peng, Jinzhu; Yu, Jie; Wang, Jie
2014-07-01
In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. PMID:24917071
Adaptive Wavefront Calibration and Control for the Gemini Planet Imager
Poyneer, L A; Veran, J
2007-02-02
Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
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
Spectrum management considerations of adaptive power control in satellite networks
NASA Technical Reports Server (NTRS)
Sawitz, P.; Sullivan, T.
1983-01-01
Adaptive power control concepts for the compensation of rain attenuation are considered for uplinks and downlinks. The performance of example power-controlled and fixed-EIRP uplinks is compared in terms of C/Ns and C/Is. Provisional conclusions are drawn with regard to the efficacy of uplink and downlink power control orbit/spectrum utilization efficiency.
Adaptive Attitude Control of the Crew Launch Vehicle
NASA Technical Reports Server (NTRS)
Muse, Jonathan
2010-01-01
An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.
Adaptive stochastic control for a class of linear systems.
NASA Technical Reports Server (NTRS)
Tse, E.; Athans, M.
1972-01-01
The problem considered in this paper deals with the control of linear discrete-time stochastic systems with unknown (possibly time-varying and random) gain parameters. The philosophy of control is based on the use of an open-loop feedback optimal (OLFO) control using a quadratic index of performance. It is shown that the OLFO system consists of (1) an identifier that estimates the system state variables and gain parameters and (2) a controller described by an 'adaptive' gain and correction term. Several qualitative properties and asymptotic properties of the OLFO adaptive system are discussed. Simulation results dealing with the control of stable and unstable third-order plants are presented. The key quantitative result is the precise variation of the control system adaptive gains as a function of the future expected uncertainty of the parameters; thus, in this problem the ordinary 'separation theorem' does not hold.
Adaptive process control using fuzzy logic and genetic algorithms
NASA Technical Reports Server (NTRS)
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Adaptive Process Control with Fuzzy Logic and Genetic Algorithms
NASA Technical Reports Server (NTRS)
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Adaptive pitch control for load mitigation of wind turbines
NASA Astrophysics Data System (ADS)
Yuan, Yuan; Tang, J.
2015-04-01
In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.
Investigation of the Multiple Model Adaptive Control (MMAC) method for flight control systems
NASA Technical Reports Server (NTRS)
1975-01-01
The application was investigated of control theoretic ideas to the design of flight control systems for the F-8 aircraft. The design of an adaptive control system based upon the so-called multiple model adaptive control (MMAC) method is considered. Progress is reported.
An adaptive learning control system for aircraft
NASA Technical Reports Server (NTRS)
Mekel, R.; Nachmias, S.
1978-01-01
A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.
Adaptive control of Hammerstein-Wiener nonlinear systems
NASA Astrophysics Data System (ADS)
Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong
2016-07-01
The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.
HIDEC F-15 adaptive engine control system flight test results
NASA Technical Reports Server (NTRS)
Smolka, James W.
1987-01-01
NASA-Ames' Highly Integrated Digital Electronic Control (HIDEC) flight test program aims to develop fully integrated airframe, propulsion, and flight control systems. The HIDEC F-15 adaptive engine control system flight test program has demonstrated that significant performance improvements are obtainable through the retention of stall-free engine operation throughout the aircraft flight and maneuver envelopes. The greatest thrust increase was projected for the medium-to-high altitude flight regime at subsonic speed which is of such importance to air combat. Adaptive engine control systems such as the HIDEC F-15's can be used to upgrade the performance of existing aircraft without resort to expensive reengining programs.
Variable neural adaptive robust control: a switched system approach.
Lian, Jianming; Hu, Jianghai; Żak, Stanislaw H
2015-05-01
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multiinput multioutput uncertain systems. The controllers incorporate a novel variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. It can determine the network structure online dynamically by adding or removing RBFs according to the tracking performance. The structure variation is systematically considered in the stability analysis of the closed-loop system using a switched system approach with the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations. PMID:25881366
Modeling-Error-Driven Performance-Seeking Direct Adaptive Control
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John
2008-01-01
This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.
Decentralized adaptive control of manipulators - Theory, simulation, and experimentation
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1989-01-01
The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.
Control of sound radiation with active/adaptive structures
NASA Technical Reports Server (NTRS)
Fuller, C. R.; Rogers, C. A.; Robertshaw, H. H.
1992-01-01
Recent research is discussed in the area of active structural acoustic control with active/adaptive structures. Progress in the areas of structural acoustics, actuators, sensors, and control approaches is presented. Considerable effort has been given to the interaction of these areas with each other due to the coupled nature of the problem. A discussion is presented on actuators bonded to or embedded in the structure itself. The actuators discussed are piezoceramic actuators and shape memory alloy actuators. The sensors discussed are optical fiber sensors, Nitinol fiber sensors, piezoceramics, and polyvinylidene fluoride sensors. The active control techniques considered are state feedback control techniques and least mean square adaptive algorithms. Results presented show that significant progress has been made towards controlling structurally radiated noise by active/adaptive means applied directly to the structure.
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.
Identification and dual adaptive control of a turbojet engine
NASA Technical Reports Server (NTRS)
Merrill, W.; Leininger, G.
1979-01-01
The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.
Hybrid adaptive ascent flight control for a flexible launch vehicle
NASA Astrophysics Data System (ADS)
Lefevre, Brian D.
For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the
Zhao, Guoliang; Li, Hongxing
2013-01-01
This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model. PMID:24453897
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.
NASA Technical Reports Server (NTRS)
Wen, John T.; Kreutz, Kenneth
1988-01-01
An approach using a globally nonsingular representation is proposed for the attitude control problem of a rigid body. The attitude dynamics are described by the nonlinear Euler equation together with the nonlinear kinematic equations which relate a representation of attitude to the angular velocity of the body. When this approach is combined with an energy-motivated Lyapunov function, a large class of globally stable attitude control laws can be derived. This class includes model-independent tracking control, model-dependent tracking control, and adaptive control, allowing tradeoffs between controller complexity, attainable performance, and available model information.
Direct adaptive control of a PUMA 560 industrial robot
NASA Technical Reports Server (NTRS)
Seraji, Homayoun; Lee, Thomas; Delpech, Michel
1989-01-01
The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.
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.
Simulation of a Reconfigurable Adaptive Control Architecture
NASA Astrophysics Data System (ADS)
Rapetti, Ryan John
A set of algorithms and software components are developed to investigate the use of a priori models of damaged aircraft to improve control of similarly damaged aircraft. An addition to Model Predictive Control called state trajectory extrapolation is also developed to deliver good handling qualities in nominal an off-nominal aircraft. System identification algorithms are also used to improve model accuracy after a damage event. Simulations were run to demonstrate the efficacy of the algorithms and software components developed herein. The effect of model order on system identification convergence and performance is also investigated. A feasibility study for flight testing is also conducted. A preliminary hardware prototype was developed, as was the necessary software to integrate the avionics and ground station systems. Simulation results show significant improvement in both tracking and cross-coupling performance when a priori control models are used, and further improvement when identified models are used.
Adaptive Attitude Control System For Space Station
NASA Technical Reports Server (NTRS)
Boussalis, Dhemetrios; Bayard, David S.; Wang, Shyh J.
1995-01-01
Report presents theoretical foundation for attitude control system for proposed Space Station Freedom in orbit around Earth. Intended to maintain space station in torque equilibrium with designated axes of its structure aligned with local vertical, local along-trajectory horizontal, and local across-trajectory horizontal axes, respectively. System required to provide desired combination of control performance and stability in presence of disturbances (e.g., variations in masses of payloads, movements of astronauts and equipment, atmospheric drag, gravitational anomalies, and interactions with docking spacecraft).
Adaptive control system for pulsed megawatt klystrons
Bolie, Victor W.
1992-01-01
The invention provides an arrangement for reducing waveform errors such as errors in phase or amplitude in output pulses produced by pulsed power output devices such as klystrons by generating an error voltage representing the extent of error still present in the trailing edge of the previous output pulse, using the error voltage to provide a stored control voltage, and applying the stored control voltage to the pulsed power output device to limit the extent of error in the leading edge of the next output pulse.
Neural and Fuzzy Adaptive Control of Induction Motor Drives
Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.
2008-06-12
This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.
Neural and Fuzzy Adaptive Control of Induction Motor Drives
NASA Astrophysics Data System (ADS)
Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.
2008-06-01
This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.
Adaptive neural network motion control of manipulators with experimental evaluations.
Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V
2014-01-01
A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910
Frequency based design of modal controllers for adaptive optics systems.
Agapito, Guido; Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
2012-11-19
This paper addresses the problem of reducing the effects of wavefront distortions in ground-based telescopes within a "Modal-Control" framework. The proposed approach allows the designer to optimize the Youla parameter of a given modal controller with respect to a relevant adaptive optics performance criterion defined on a "sampled" frequency domain. This feature makes it possible to use turbulence/vibration profiles of arbitrary complexity (even empirical power spectral densities from data), while keeping the controller order at a moderate value. Effectiveness of the proposed solution is also illustrated through an adaptive optics numerical simulator. PMID:23187567
Adaptive Control of Truss Structures for Gossamer Spacecraft
NASA Technical Reports Server (NTRS)
Yang Bong-Jun; Calise, anthony J.; Craig, James I.; Whorton, Mark S.
2007-01-01
Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.
Dynamical singularities in adaptive delayed-feedback control.
Saito, Asaki; Konishi, Keiji
2011-09-01
We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398
Extremum seeking-based adaptive control for electromagnetic actuators
NASA Astrophysics Data System (ADS)
Benosman, Mouhacine; Atınç, Gökhan M.
2015-03-01
In this paper, we present a learning-based adaptive method to solve the problem of robust trajectory tracking for electromagnetic actuators. We merge a nonlinear backstepping controller that ensures bounded input/bounded states stability, with a multi-variable extremum seeking model-free learning algorithm. The learning algorithm is used to estimate online the uncertain parameters of the model, in this sense, we propose a learning-based adaptive controller. We present a proof of stability of this learning-based nonlinear controller when considering uncertainties with linear parametrisation. The efficiency of this approach is shown on a numerical example.
On Using Exponential Parameter Estimators with an Adaptive Controller
NASA Technical Reports Server (NTRS)
Patre, Parag; Joshi, Suresh M.
2011-01-01
Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.
Inherent robustness of discrete-time adaptive control systems
NASA Technical Reports Server (NTRS)
Ma, C. C. H.
1986-01-01
Global stability robustness with respect to unmodeled dynamics, arbitrary bounded internal noise, as well as external disturbance is shown to exist for a class of discrete-time adaptive control systems when the regressor vectors of these systems are persistently exciting. Although fast adaptation is definitely undesirable, so far as attaining the greatest amount of global stability robustness is concerned, slow adaptation is shown to be not necessarily beneficial. The entire analysis in this paper holds for systems with slowly varying return difference matrices; the plants in these systems need not be slowly varying.
Digital adaptive control laws for the F-8
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Harvey, C. A.
1976-01-01
NASA is conducting a flight control research program in digital fly-by-wire technology using a modified F-8C aircraft. The first phase of this program used Apollo hardware to demonstrate the practicality of digital fly-by-wire in an actual test vehicle. For the second phase, conventional aircraft sensors and a large floating point digital computer are being utilized to test advanced control laws and redundancy concepts. As part of NASA's research in digital fly-by-wire technology, Honeywell developed digital adaptive flight control laws for flight test in the F-8C. Adaptation of the control laws was to be based on information sensed from conventional aircraft sensors excluding air data. The control laws were constrained to use only existing elevator, rudder, and ailerons as control effectors, each powered by existing actuators. Three adaptive control laws were successfully designed using maximum likelihood estimation, a Liapunov stable model tracker and a self-excited limit cycle concept. The maximum likelihood estimation design was selected as the most promising because of its capability to identify more than surface effectiveness parameters. The adaptive concepts, the control laws and comparisons of predicted performance are described.
Study on rule-based adaptive fuzzy excitation control technology
NASA Astrophysics Data System (ADS)
Zhao, Hui; Wang, Hong-jun; Liu, Lu-yuan; Yue, You-jun
2008-10-01
Power system is a kind of typical non-linear system, it is hard to achieve excellent control performance with conventional PID controller under different operating conditions. Fuzzy parameter adaptive PID exciting controller is very efficient to overcome the influence of tiny disturbances, but the performance of the control system will be worsened when operating conditions of the system change greatly or larger disturbances occur. To solve this problem, this article presents a rule adaptive fuzzy control scheme for synchronous generator exciting system. In this scheme the control rule adaptation is implemented by regulating the value of parameter di under the given proportional divisors K1, K2 and K3 of fuzzy sets Ai and Bi. This rule adaptive mechanism is constituted by two groups of original rules about the self-generation and self-correction of the control rule. Using two groups of rules, the control rule activated by status 1 and 2 in figure 2 system can be regulated automatically and simultaneously at the time instant k. The results from both theoretical analysis and simulation show that the presented scheme is effective and feasible and possesses good performance.
Adaptive Power Control for Space Communications
NASA Technical Reports Server (NTRS)
Thompson, Willie L., II; Israel, David J.
2008-01-01
This paper investigates the implementation of power control techniques for crosslinks communications during a rendezvous scenario of the Crew Exploration Vehicle (CEV) and the Lunar Surface Access Module (LSAM). During the rendezvous, NASA requires that the CEV supports two communication links: space-to-ground and crosslink simultaneously. The crosslink will generate excess interference to the space-to-ground link as the distances between the two vehicles decreases, if the output power is fixed and optimized for the worst-case link analysis at the maximum distance range. As a result, power control is required to maintain the optimal power level for the crosslink without interfering with the space-to-ground link. A proof-of-concept will be described and implemented with Goddard Space Flight Center (GSFC) Communications, Standard, and Technology Lab (CSTL).
Adapting Inspection Data for Computer Numerical Control
NASA Technical Reports Server (NTRS)
Hutchison, E. E.
1986-01-01
Machining time for repetitive tasks reduced. Program converts measurements of stub post locations by coordinate-measuring machine into form used by numerical-control computer. Work time thus reduced by 10 to 15 minutes for each post. Since there are 600 such posts on each injector, time saved per injector is 100 to 150 hours. With modifications this approach applicable to machining of many precise holes on large machine frames and similar objects.
Adaptive control of large space structures using recursive lattice filters
NASA Technical Reports Server (NTRS)
Goglia, G. L.
1985-01-01
The use of recursive lattice filters for identification and adaptive control of large space structures was studied. Lattice filters are used widely in the areas of speech and signal processing. Herein, they are used to identify the structural dynamics model of the flexible structures. This identified model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures control is engaged. This type of validation scheme prevents instability when the overall loop is closed. The results obtained from simulation were compared to those obtained from experiments. In this regard, the flexible beam and grid apparatus at the Aerospace Control Research Lab (ACRL) of NASA Langley Research Center were used as the principal candidates for carrying out the above tasks. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods.
Adaptive control of an automatic transmission
Lentz, C.A.; Runde, J.K.; Hunter, J.H.; Wiles, C.R.
1991-12-10
This patent describes a vehicular automatic transmission in which a shift from a first speed ratio to a second speed ratio is carried out through concurrent disengagement of a fluid pressure operated off-going torque transmitting device associated with the first speed ratio and engagement of a fluid pressure operated oncoming torque transmitting device associated with the second speed ratio, a method of automatically shifting the transmission. It comprises disengaging the off-going torque transmitting device by reducing its pre-shift engagement pressure, engaging the on-coming torque transmitting device by supplying it with hydraulic pressure according to a pressure command having a predetermined initial value, and thereafter initiating a closed-loop control of the pressure command based on a predefined pattern of input and output speeds chosen to yield high quality shifting, the pressure command achieving a final value upon completion of the closed-loop control; comparing a difference between the final value of the pressure command and the pressure command at the initiation of the closed-loop control with a threshold to detect an aberration; and if the difference exceeds the threshold, adjusting the predetermined initial value by an amount which is a function of the difference so that on the next shift the pressure command will have an initial value which is substantially correct for achieving the predefined pattern of input and output speeds.
Adaptive landing gear concept—feedback control validation
NASA Astrophysics Data System (ADS)
Mikulowski, Grzegorz M.; Holnicki-Szulc, Jan
2007-12-01
The objective of this paper is to present an integrated feedback control concept for adaptive landing gears (ALG) and its experimental validation. Aeroplanes are subjected to high dynamic loads as a result of the impact during each landing. Classical landing gears, which are in common use, are designed in accordance with official regulations in a way that ensures the optimal energy dissipation for the critical (maximum) sink speed. The regulations were formulated in order to ensure the functional capability of the landing gears during an emergency landing. However, the landing gears, whose characteristics are optimized for these critical conditions, do not perform well under normal impact conditions. For that situation it is reasonable to introduce a system that would adapt the characteristics of the landing gears according to the sink speed of landing. The considered system assumes adaptation of the damping force generated by the landing gear, which would perform optimally in an emergency situation and would adapt itself for regular landings as well. This research covers the formulation and design of the control algorithms for an adaptive landing gear based on MR fluid, implementation of the algorithms on an FPGA platform and experimental verification on a lab-scale landing gear device. The main challenge of the research was to develop a control methodology that could operate effectively within 50 ms, which is assumed to be the total duration of the phenomenon. The control algorithm proposed in this research was able to control the energy dissipation process on the experimental stand.
NASA Technical Reports Server (NTRS)
Baer-Riedhart, Jennifer L.; Landy, Robert J.
1987-01-01
The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.
Residual mode filters and adaptive control in large space structures
NASA Technical Reports Server (NTRS)
Davidson, Roger A.; Balas, Mark J.
1989-01-01
One of the most difficult problems in controlling large systems and structures is compensating for the destructive interaction which can occur between the reduced-order model (ROM) of the plant, which is used by the controller, and the unmodeled dynamics of the plant, often called the residual modes. The problem is more significant in the case of large space structures because their naturally light damping and high performance requirements lead to more frequent, destructive residual mode interaction (RMI). Using the design/compensation technique of residual mode filters (RMF's), effective compensation of RMI can be accomplished in a straightforward manner when using linear controllers. The use of RMF's has been shown to be effective for a variety of large structures, including a space-based laser and infinite dimensional systems. However, the dynamics of space structures is often uncertain and may even change over time due to on-orbit erosion from space debris and corrosive chemicals in the upper atmosphere. In this case, adaptive control can be extremely beneficial in meeting the performance requirements of the structure. Adaptive control for large structures is also based on ROM's and so destructive RMI may occur. Unfortunately, adaptive control is inherently nonlinear, and therefore the known results of RMF's cannot be applied. The purpose is to present the results of new research showing the effects of RMI when using adaptive control and the work which will hopefully lead to RMF compensation of this problem.
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.
Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.
Zhang, Yanjun; Tao, Gang; Chen, Mou
2016-09-01
This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method. PMID:26285223
Adaptive mass expulsion attitude control system
NASA Technical Reports Server (NTRS)
Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)
2001-01-01
An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.
Adapting End Host Congestion Control for Mobility
NASA Technical Reports Server (NTRS)
Eddy, Wesley M.; Swami, Yogesh P.
2005-01-01
Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP.
Adaptive independent joint control of manipulators - Theory and experiment
NASA Technical Reports Server (NTRS)
Seraji, H.
1988-01-01
The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.
Adaptive control system having hedge unit and related apparatus and methods
NASA Technical Reports Server (NTRS)
Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)
2003-01-01
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Adaptive control system having hedge unit and related apparatus and methods
NASA Technical Reports Server (NTRS)
Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)
2007-01-01
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Adaptive control of large space structures using recursive lattice filters
NASA Technical Reports Server (NTRS)
Sundararajan, N.; Goglia, G. L.
1985-01-01
The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.
Adaptive neural PD control with semiglobal asymptotic stabilization guarantee.
Pan, Yongping; Yu, Haoyong; Er, Meng Joo
2014-12-01
This paper proves that adaptive neural plus proportional-derivative (PD) control can lead to semiglobal asymptotic stabilization rather than uniform ultimate boundedness for a class of uncertain affine nonlinear systems. An integral Lyapunov function-based ideal control law is introduced to avoid the control singularity problem. A variable-gain PD control term without the knowledge of plant bounds is presented to semiglobally stabilize the closed-loop system. Based on a linearly parameterized raised-cosine radial basis function neural network, a key property of optimal approximation is exploited to facilitate stability analysis. It is proved that the closed-loop system achieves semiglobal asymptotic stability by the appropriate choice of control parameters. Compared with previous adaptive approximation-based semiglobal or asymptotic stabilization approaches, our approach not only significantly simplifies control design, but also relaxes constraint conditions on the plant. Two illustrative examples have been provided to verify the theoretical results. PMID:25420247
Optimal wavefront control for adaptive segmented mirrors
NASA Technical Reports Server (NTRS)
Downie, John D.; Goodman, Joseph W.
1989-01-01
A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.
Aryl Hydrocarbon Receptor Control of Adaptive Immunity
2013-01-01
The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that belongs to the family of basic helix-loop-helix transcription factors. Although the AhR was initially recognized as the receptor mediating the pathologic effects of dioxins and other pollutants, the activation of AhR by endogenous and environmental factors has important physiologic effects, including the regulation of the immune response. Thus, the AhR provides a molecular pathway through which environmental factors modulate the immune response in health and disease. In this review, we discuss the role of AhR in the regulation of the immune response, the source and chemical nature of AhR ligands, factors controlling production and degradation of AhR ligands, and the potential to target the AhR for therapeutic immunomodulation. PMID:23908379
An adaptable Boolean net trainable to control a computing robot
Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.
1999-03-22
We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits.
Adaptive neural network consensus based control of robot formations
NASA Astrophysics Data System (ADS)
Guzey, H. M.; Sarangapani, Jagannathan
2013-05-01
In this paper, adaptive consensus based formation control scheme is derived for mobile robots in a pre-defined formation when full dynamics of the robots which include inertia, Corolis, and friction vector are considered. It is shown that dynamic uncertainties of robots can make overall formation unstable when traditional consensus scheme is utilized. In order to estimate the affine nonlinear robot dynamics, a NN based adaptive scheme is utilized. In addition to this adaptive feedback control input, an additional control input is introduced based on the consensus approach to make the robots keep their desired formation. Subsequently, the outer consensus loop is redesigned for reduced communication. Lyapunov theory is used to show the stability of overall system. Simulation results are included at the end.
A discrete-time adaptive control scheme for robot manipulators
NASA Technical Reports Server (NTRS)
Tarokh, M.
1990-01-01
A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.
NASA Technical Reports Server (NTRS)
Kopasakis, George
1997-01-01
Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
Mechanisms of Motor Adaptation in Reactive Balance Control
Welch, Torrence D. J.; Ting, Lena H.
2014-01-01
Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM) excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations. PMID:24810991
Mechanisms of motor adaptation in reactive balance control.
Welch, Torrence D J; Ting, Lena H
2014-01-01
Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM) excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations. PMID:24810991
Environment Adaptive Heading Control for an Autonomous Unmanned Helicopter
NASA Astrophysics Data System (ADS)
Nakanishi, Hiroaki; Kanata, Sayaka; Sawaragi, Tetsuo; Horiguchi, Yukio
To develop flying rescue robots using autonomous unmanned helicopters, it is necessary to improve performance and reliability of flight control systems. Adaptation against the environmental changes, such as wind, has very important role. In this paper, adaptive heading (yaw) control for an autonomous helicopter is proposed. Roll angle and roll rate are used to determine desired yaw angle. Therefore, roll dynamics and yaw dynamics are coupled and stable dutch roll is induced to change the yaw angle corresponding to wind direction or the direction of the helicopter's motion. Results of flight experiments show the effectiveness of the proposed method.
Adaptive control of surface finish in automated turning processes
NASA Astrophysics Data System (ADS)
García-Plaza, E.; Núñez, P. J.; Martín, A. R.; Sanz, A.
2012-04-01
The primary aim of this study was to design and develop an on-line control system of finished surfaces in automated machining process by CNC turning. The control system consisted of two basic phases: during the first phase, surface roughness was monitored through cutting force signals; the second phase involved a closed-loop adaptive control system based on data obtained during the monitoring of the cutting process. The system ensures that surfaces roughness is maintained at optimum values by adjusting the feed rate through communication with the PLC of the CNC machine. A monitoring and adaptive control system has been developed that enables the real-time monitoring of surface roughness during CNC turning operations. The system detects and prevents faults in automated turning processes, and applies corrective measures during the cutting process that raise quality and reliability reducing the need for quality control.
Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks
NASA Technical Reports Server (NTRS)
Jorgensen, Charles C.
1997-01-01
A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.
The design of digital-adaptive controllers for VTOL aircraft
NASA Technical Reports Server (NTRS)
Stengel, R. F.; Broussard, J. R.; Berry, P. W.
1976-01-01
Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.
Adaptive-Control Experiments On A Large Flexible Structure
NASA Technical Reports Server (NTRS)
Ih, Che-Hang C.; Bayard, David S.; Wang, Shyh J.; Eldred, Daniel B.
1990-01-01
Antennalike flexible structure built for research in advanced technology including suppression of vibrations and control of initial deflections. Structure instrumented with sensors and actuators connected to digital electronic control system, programmed with control algorithms to be tested. Particular attention in this research focused on direct model-reference adaptive-control algorithm based on command generator tracker theory. Built to exhibit multiple vibrational modes, low modal frequencies, and low structural damping. Made three-dimensional so complicated interactions among components of structure and control system investigated.
Model-free adaptive control of advanced power plants
Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang
2015-08-18
A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
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.
Adaptive support vector regression for UAV flight control.
Shin, Jongho; Jin Kim, H; Kim, Youdan
2011-01-01
This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model. PMID:20970303
Adaptive backstepping slide mode control of pneumatic position servo system
NASA Astrophysics Data System (ADS)
Ren, Haipeng; Fan, Juntao
2016-06-01
With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.
An adaptive robust controller for time delay maglev transportation systems
NASA Astrophysics Data System (ADS)
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
2012-12-01
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
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…
Adaptive Insecure Attachment and Resource Control Strategies during Middle Childhood
ERIC Educational Resources Information Center
Chen, Bin-Bin; Chang, Lei
2012-01-01
By integrating the life history theory of attachment with resource control theory, the current study examines the hypothesis that insecure attachment styles reorganized in middle childhood are alternative adaptive strategies used to prepare for upcoming competition with the peer group. A sample of 654 children in the second through seventh grades…
Variable Neural Adaptive Robust Control: A Switched System Approach
Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.
2015-05-01
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.
Adaptive synchronization and pinning control of colored networks
NASA Astrophysics Data System (ADS)
Wu, Zhaoyan; Xu, Xin-Jian; Chen, Guanrong; Fu, Xinchu
2012-12-01
A colored network model, corresponding to a colored graph in mathematics, is used for describing the complexity of some inter-connected physical systems. A colored network is consisted of colored nodes and edges. Colored nodes may have identical or nonidentical local dynamics. Colored edges between any pair of nodes denote not only the outer coupling topology but also the inner interactions. In this paper, first, synchronization of edge-colored networks is studied from adaptive control and pinning control approaches. Then, synchronization of general colored networks is considered. To achieve synchronization of a colored network to an arbitrarily given orbit, open-loop control, pinning control and adaptive coupling strength methods are proposed and tested, with some synchronization criteria derived. Finally, numerical examples are given to illustrate theoretical results.
A fundamental aeroservoelastic study combining unsteady CFD with adaptive control
NASA Technical Reports Server (NTRS)
Friedmann, P.; Guillot, Damien M.
1994-01-01
This paper describes a two-dimensional aeroservoelastic study in the time domain. The model, which is based on exact inviscid aerodynamics, correctly represents the large amplitude motions and the associated strong shock dynamics in the transonic regime. The aeroservoelastic system consists of a two degree-of-freedom airfoil with a trailing edge control surface. Using first-order actuator dynamics, a digital adaptive controller is applied to provide active flutter suppression. Comparisons between time-responses of the open-loop and closed loop systems show the ability of the trailing edge control surface to suppress non-linear transonic aeroelastic phenomena. A relation between actuator dynamics, sampling time-step and limits on the flap deflection angle to guarantee the effectiveness of the adaptive controller was demonstrated by the results generated.
Experimental implementation of adaptive control for flexible space structures
NASA Technical Reports Server (NTRS)
Mcgraw, Gary A.
1988-01-01
On-going research at The Aerospace Corporation studying the feasibility of applying adaptive control methodologies to the control of flexible space structures is described. A laboratory testbed was established to test system identification and control approaches. The laboratory set-up and controller design approach are discussed. The ARX least squares parameter estimation technique is analyzed in terms of frequency domain transfer function bias error. This analysis approach enables the determination of the effects of sampling rate, sensor type, and data prefiltering on the estimation performance. The ability to identify space structure dynamics over a range of frequencies is shown to be heavily dependent on these factors.
Model reference adaptive attitude control of spacecraft using reaction wheels
NASA Technical Reports Server (NTRS)
Singh, Sahjendra N.
1986-01-01
A nonlinear model reference adaptive control law for large angle rotational maneuvers of spacecraft using reaction wheels in the presence of uncertainty is presented. The derivation of control law does not require any information on the values of the system parameters and the disturbance torques acting on the spacecraft. The controller includes a dynamic system in the feedback path. The control law is a nonlinear function of the attitude error, the rate of the attitude error, and the compensator state. Simulation results are prsented to show that large angle rotational maneuvers can be performed in spite of the uncertainty in the system.
Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems
NASA Technical Reports Server (NTRS)
Esogbue, Augustine O.
1998-01-01
The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of
A Comprehensive Robust Adaptive Controller for Gust Load Alleviation
Quagliotti, Fulvia
2014-01-01
The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required. PMID:24688411
Implementation of Adaptive Digital Controllers on Programmable Logic Devices
NASA Technical Reports Server (NTRS)
Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Ormsby, John (Technical Monitor)
2002-01-01
Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing (DSP) functions. Such capability also makes and FPGA a suitable platform for the digital implementation of closed loop controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance in a compact form-factor. Other researchers have presented the notion that a second order digital filter with proportional-integral-derivative (PID) control functionality can be implemented in an FPGA. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSF) devices. Our goal is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. Meeting our goals requires alternative compact implementation of such functionality to withstand the harsh environment encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching these goals.
NASA Astrophysics Data System (ADS)
Senthilkumar, P.; Dayananda, G. N.; Umapathy, M.; Shankar, V.
2012-01-01
This paper presents an experimental investigation of position control of a shape memory alloy (SMA) wire actuator with adaptive and modulated adaptive controllers. The transfer function model of the SMA wire actuator is determined from the experimental open loop response. Adaptive controllers, namely LMS-GSPI, RLS-GSPI and Kalman-GSPI, and modulated adaptive controllers using pulse width modulation (PWM) are designed. The performances of these controllers are experimentally investigated for the position control of an SMA wire actuator with and without thermal disturbance. Experimental results demonstrate that the modulated adaptive controllers outperform adaptive controllers.
Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.
Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan
2016-02-22
We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved. PMID:26906999
F-8C adaptive control law refinement and software development
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.
1981-01-01
An explicit adaptive control algorithm based on maximum likelihood estimation of parameters was designed. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm was implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer, surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software.
NASA Astrophysics Data System (ADS)
D'Amato, Anthony M.
Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros. The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system. RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured. Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate
Robust observer-based adaptive fuzzy sliding mode controller
NASA Astrophysics Data System (ADS)
Oveisi, Atta; Nestorović, Tamara
2016-08-01
In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.
A novel adaptive force control method for IPMC manipulation
NASA Astrophysics Data System (ADS)
Hao, Lina; Sun, Zhiyong; Li, Zhi; Su, Yunquan; Gao, Jianchao
2012-07-01
IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable.
Implementation of Adaptive Digital Controllers on Programmable Logic Devices
NASA Technical Reports Server (NTRS)
Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Montenegro, Justino (Technical Monitor)
2002-01-01
Much has been made of the capabilities of Field Programmable Gate Arrays (FPGA's) in the hardware implementation of fast digital signal processing functions. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used Proportional-Integral-Derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a Digital Signal Processor (DSP) device or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using DSP devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, Pulse Width Modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacemap. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive-control algorithm
Implementation of Adaptive Digital Controllers on Programmable Logic Devices
NASA Technical Reports Server (NTRS)
Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)
2002-01-01
Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment
Dynamic data-driven sensor network adaptation for border control
NASA Astrophysics Data System (ADS)
Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna
2013-06-01
Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.
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.
Adaptive Control of a Transport Aircraft Using Differential Thrust
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan
2009-01-01
The paper presents an adaptive control technique for a damaged large transport aircraft subject to unknown atmospheric disturbances such as wind gust or turbulence. It is assumed that the damage results in vertical tail loss with no rudder authority, which is replaced with a differential thrust input. The proposed technique uses the adaptive prediction based control design in conjunction with the time scale separation principle, based on the singular perturbation theory. The application of later is necessitated by the fact that the engine response to a throttle command is substantially slow that the angular rate dynamics of the aircraft. It is shown that this control technique guarantees the stability of the closed-loop system and the tracking of a given reference model. The simulation example shows the benefits of the approach.
Decentralized adaptive control of robot manipulators with robust stabilization design
NASA Technical Reports Server (NTRS)
Yuan, Bau-San; Book, Wayne J.
1988-01-01
Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.
Network Adaptive Deadband: NCS Data Flow Control for Shared Networks
Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín
2012-01-01
This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556
On fractional order composite model reference adaptive control
NASA Astrophysics Data System (ADS)
Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong
2016-08-01
This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.
A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance
NASA Astrophysics Data System (ADS)
Sreekumar, Muthuswamy
2016-03-01
Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.
Adaptation with disturbance attenuation in nonlinear control systems
Basar, T.
1997-12-31
We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.
A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance
NASA Astrophysics Data System (ADS)
Sreekumar, Muthuswamy
2016-07-01
Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.
Nonlinear adaptive control of an elastic robotic arm
NASA Technical Reports Server (NTRS)
Singh, S. N.
1986-01-01
An approach to control of a class of nonlinear flexible robotic systems is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. An adaptive torquer control law is derived for controlling the joint angles. This controller includes a dynamic system in the feedback path, requires only joint angle and rate for feedback, and asymptotically decomposes the elastic dynamics into two subsystems representing the transverse vibrations of the elastic link in two orthogonal planes. To damp out the elastic vibration, a force control law using modal feedback is synthesized. The combination of the torque and force control laws accomplishes joint angle control and elastic mode stabilization.
Adaptive state estimation for control of flexible structures
NASA Technical Reports Server (NTRS)
Chen, Chung-Wen; Huang, Jen-Kuang
1990-01-01
This paper proposes a new approach of obtaining adaptive state estimation of a system in the presence of unknown system disturbances and measurement noise. In the beginning, a non-optimal Kalman filter with arbitrary initial guess for the process and measurement noises is implemented. At the same time, an adaptive transversal predictor (ATP) based on the recursive least-squares (RLS) algorithm is used to yield optimal one- to p- step-ahead output predictions using the previous input/output data. Referring to these optimal predictions the Kalman filter gain is updated and the performance of the state estimation is thus improved. If forgetting factor is implemented in the recursive least-squares algorithm, this method is also capable of dealing with the situation when the noise statistics are slowly time-varying. This feature makes this new approach especially suitable for the control of flexible structures. A numerical example demonstrates the feasibility of this real time adaptive state estimation method.
Beaconless adaptive-optics technique for HEL beam control
NASA Astrophysics Data System (ADS)
Khizhnyak, Anatoliy; Markov, Vladimir
2016-05-01
Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.
Adaptive control of Space Station during nominal operations with CMGs. [Control Moment Gyroscopes
NASA Technical Reports Server (NTRS)
Bishop, R. H.; Paynter, S. J.; Sunkel, J. W.
1991-01-01
An adaptive control approach is investigated for the Space Station. The main components of the adaptive controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is the Space Station baseline control law. The control gain calculation is based on linear quadratic regulator theory with eigenvalue placement in a vertical strip. The parameter identification scheme is a real-time recursive extended Kalman filter which estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to compute accurate estimates of the Space Station inertias during nominal CMG (control moment gyro) operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.
An adaptive fuzzy controller for permanent-magnet AC servo drives
Le-Huy, H.
1995-12-31
This paper presents a theoretical study on a model-reference adaptive fuzzy logic controller for vector-controlled permanent-magnet ac servo drives. In the proposed system, fuzzy logic is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The results are compared with that provided by a non-adaptive fuzzy controller. The implementation of proposed adaptive fuzzy controller is discussed.
Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems
NASA Technical Reports Server (NTRS)
Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.
1979-01-01
The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.
Robust adaptive backstepping control for reentry reusable launch vehicles
NASA Astrophysics Data System (ADS)
Wang, Zhen; Wu, Zhong; Du, Yijiang
2016-09-01
During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.
Towards feasible and effective predictive wavefront control for adaptive optics
Poyneer, L A; Veran, J
2008-06-04
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.
Adaptive control of systems with unknown time delays
NASA Astrophysics Data System (ADS)
Nelson, James P.
Control systems, on earth or in outer-space, may exhibit time delays in their dynamic behavior. Aerospace control systems must be able to operate in the presence of time delays both internal to the system and in its inputs and outputs. These delays are often introduced via systems controlled through a network, by information, energy or mass transport phenomena, but can also be caused by computer processing time or by the accumulation of time lags in a number of simple dynamic systems connected in series. When a dynamic system is subject to a time delay, unlike other parameters, this affects the temporal characteristics of the system and exact control over system operation cannot be strictly implemented. Systems with significant time delays are difficult to control using standard feedback controllers. The United States Air Force Research Laboratory (AFRL) is considering the use of router-based data networks on-board next generation satellites and in decentralized control architectures. This approach has the potential to introduce non-constant and non-deterministic communications delays into feedback control loops that make use of these data networks. The desire for rapid deployment of new spacecraft architectures will also introduce many other control issues as the rigorous measurement, calibration and performance tests usually conducted on spacecraft systems to develop a highly precise dynamic model will need to be drastically shortened due to the desired abbreviated build and launch schedule. Due to limited testing and system identification, the spacecraft model will have uncertainties/perturbations from the actual plant. This will require a controller that can robustly control the non-linear dynamic model with limited plant knowledge. The problems created by the control of time delay systems and the limited plant knowledge nature of the systems of interest leads us to the concept of adaptive control. Adaptive control makes adjustment of the controllers
Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller
NASA Astrophysics Data System (ADS)
Engel, E.; Kovalev, I. V.; Karandeev, D.
2015-10-01
The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.
Minimal control synthesis adaptive control of nonlinear systems: utilizing the properties of chaos.
di Bernardo, M; Stoten, D P
2006-09-15
This paper discusses a novel approach to the control of chaos based on the use of the adaptive minimal control synthesis algorithm. The strategies presented are based on the explicit exploitation of different properties of chaotic systems including the boundedness of the chaotic attractors and their topological transitivity (or ergodicity). It is shown that chaos can be exploited to synthesize more efficient control techniques for nonlinear systems. For instance, by using the ergodicity of the chaotic trajectory, we show that a local adaptive control strategy can be used to synthesize a global controller. An application is to the swing-up control of a double inverted pendulum. PMID:16893794
Visuomotor Control of Human Adaptive Locomotion: Understanding the Anticipatory Nature
Higuchi, Takahiro
2013-01-01
To maintain balance during locomotion, the central nervous system (CNS) accommodates changes in the constraints of spatial environment (e.g., existence of an obstacle or changes in the surface properties). Locomotion while modifying the basic movement patterns in response to such constraints is referred to as adaptive locomotion. The most powerful means of ensuring balance during adaptive locomotion is to visually perceive the environmental properties at a distance and modify the movement patterns in an anticipatory manner to avoid perturbation altogether. For this reason, visuomotor control of adaptive locomotion is characterized, at least in part, by its anticipatory nature. The purpose of the present article is to review the relevant studies which revealed the anticipatory nature of the visuomotor control of adaptive locomotion. The anticipatory locomotor adjustments for stationary and changeable environment, as well as the spatio-temporal patterns of gaze behavior to support the anticipatory locomotor adjustments are described. Such description will clearly show that anticipatory locomotor adjustments are initiated when an object of interest (e.g., a goal or obstacle) still exists in far space. This review also show that, as a prerequisite of anticipatory locomotor adjustments, environmental properties are accurately perceived from a distance in relation to individual’s action capabilities. PMID:23720647
Effect of prism adaptation on thermoregulatory control in humans.
Calzolari, Elena; Gallace, Alberto; Moseley, G Lorimer; Vallar, Giuseppe
2016-01-01
The physiological regulation of skin temperature can be modulated not only by autonomic brain regions, but also by a network of higher-level cortical areas involved in the maintenance of a coherent representation of the body. In this study we assessed in healthy participants if the sensorimotor changes taking place during motor adaptation to the lateral displacement of the visual scene induced by wearing prismatic lenses (prism adaptation, PA), and the aftereffects, after prisms' removal, on the ability to process spatial coordinates, were associated with skin temperature regulation changes. We found a difference in thermoregulatory control as a function of the direction of the prism-induced displacement of the visual scene, and the subsequent sensorimotor adaptation. After PA to rightward displacing lenses, with leftward aftereffects (the same directional procedure efficaciously used for ameliorating left spatial neglect in right-brain-damaged patients) the hands' temperature decreased. Conversely, after adaptation to neutral lenses, and PA to leftward displacing lenses, with rightward aftereffects, the temperature of both hands increased. These results suggest a lateral asymmetry in the effects of PA on skin temperature regulation, and a relationship between body spatial representations and homeostatic control in humans. PMID:26354443
Geometry adaptive control of a composite reflector using PZT actuator
NASA Astrophysics Data System (ADS)
Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang
2015-04-01
Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.
An adaptive learning control system for large flexible structures
NASA Technical Reports Server (NTRS)
Thau, F. E.
1985-01-01
The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.
Adaptive and predictive control of a simulated robot arm.
Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo
2013-06-01
In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs). PMID:23627657
Adaptive subwavelength control of nano-optical fields.
Aeschlimann, Martin; Bauer, Michael; Bayer, Daniela; Brixner, Tobias; García de Abajo, F Javier; Pfeiffer, Walter; Rohmer, Martin; Spindler, Christian; Steeb, Felix
2007-03-15
Adaptive shaping of the phase and amplitude of femtosecond laser pulses has been developed into an efficient tool for the directed manipulation of interference phenomena, thus providing coherent control over various quantum-mechanical systems. Temporal resolution in the femtosecond or even attosecond range has been demonstrated, but spatial resolution is limited by diffraction to approximately half the wavelength of the light field (that is, several hundred nanometres). Theory has indicated that the spatial limitation to coherent control can be overcome with the illumination of nanostructures: the spatial near-field distribution was shown to depend on the linear chirp of an irradiating laser pulse. An extension of this idea to adaptive control, combining multiparameter pulse shaping with a learning algorithm, demonstrated the generation of user-specified optical near-field distributions in an optimal and flexible fashion. Shaping of the polarization of the laser pulse provides a particularly efficient and versatile nano-optical manipulation method. Here we demonstrate the feasibility of this concept experimentally, by tailoring the optical near field in the vicinity of silver nanostructures through adaptive polarization shaping of femtosecond laser pulses and then probing the lateral field distribution by two-photon photoemission electron microscopy. In this combination of adaptive control and nano-optics, we achieve subwavelength dynamic localization of electromagnetic intensity on the nanometre scale and thus overcome the spatial restrictions of conventional optics. This experimental realization of theoretical suggestions opens a number of perspectives in coherent control, nano-optics, nonlinear spectroscopy, and other research fields in which optical investigations are carried out with spatial or temporal resolution. PMID:17361179
Application of network control systems for adaptive optics
NASA Astrophysics Data System (ADS)
Eager, Robert J.
2008-04-01
The communication architecture for most pointing, tracking, and high order adaptive optics control systems has been based on a centralized point-to-point and bus based approach. With the increased use of larger arrays and multiple sensors, actuators and processing nodes, these evolving systems require decentralized control, modularity, flexibility redundancy, integrated diagnostics, dynamic resource allocation, and ease of maintenance to support a wide range of experiments. Network control systems provide all of these critical functionalities. This paper begins with a quick overview of adaptive optics as a control system and communication architecture. It then provides an introduction to network control systems, identifying the key design areas that impact system performance. The paper then discusses the performance test results of a fielded network control system used to implement an adaptive optics system comprised of: a 10KHz, 32x32 spatial selfreferencing interferometer wave front sensor, a 705 channel "Tweeter" deformable mirror, a 177 channel "Woofer" deformable mirror, ten processing nodes, and six data acquisition nodes. The reconstructor algorithm utilized a modulo-2pi wave front phase measurement and a least-squares phase un-wrapper with branch point correction. The servo control algorithm is a hybrid of exponential and infinite impulse response controllers, with tweeter-to-woofer saturation offloading. This system achieved a first-pixel-out to last-mirror-voltage latency of 86 microseconds, with the network accounting for 4 microseconds of the measured latency. Finally, the extensibility of this architecture will be illustrated, by detailing the integration of a tracking sub-system into the existing network.
Adaptive model predictive process control using neural networks
Buescher, K.L.; Baum, C.C.; Jones, R.D.
1997-08-19
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.
Adaptive model predictive process control using neural networks
Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.
1997-01-01
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems
NASA Astrophysics Data System (ADS)
Volyanskyy, Kostyantyn Y.
Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance
Discrete-time minimal control synthesis adaptive algorithm
NASA Astrophysics Data System (ADS)
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
2010-12-01
This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.
High-speed train control based on multiple-model adaptive control with second-level adaptation
NASA Astrophysics Data System (ADS)
Zhou, Yonghua; Zhang, Zhenlin
2014-05-01
Speed uplift has become the leading trend for the development of current railway traffic. Ideally, under the high-speed transportation infrastructure, trains run at specified positions with designated speeds at appointed times. In view of the faster adaptation ability of multiple-model adaptive control with second-level adaptation (MMAC-SLA), we propose one type of MMAC-SLA for a class of nonlinear systems such as cascaded vehicles. By using an input decomposition technique, the corresponding stability proof is solved for the proposed MMAC-SLA, which synthesises the control signals from the weighted multiple models. The control strategy is utilised to challenge the position and speed tracking of high-speed trains with uncertain parameters. The simulation results demonstrate that the proposed MMAC-SLA can achieve small tracking errors with moderate in-train forces incurred under the control of flattening input signals with practical enforceability. This study also provides a new idea for the control of in-train forces by tracking the positions and speeds of cars while considering power constraints.
Adaptive control of redundant multilink robot using fuzzy logic
NASA Astrophysics Data System (ADS)
Su, X.; Mitra, Sunanda
1993-12-01
A new approach to fuzzy distance and restriction measures is used to obtain the appropriate orientations of the links for avoiding obstacles in the robot trajectories. This approach eliminates the classical task of solving highly coupled, nonlinear equations describing the ill- posed inverse problems of multilink robot motion at a much less demanding computational time. Such clear advantage of fuzzy logic based adaptive controller are illustrated by simulation results of guidance of a multilink robot in target positioning and trajectories tracking. The simulation results involve a three-link robot arm with capability of moving from one position to any desired position and tracking a defined trajectories accurately. A modified fuzzy rule based distance measure allows the robot to follow trajectories within hitting the obstacles in the path. The simulation results indicate the advantage of fuzzy logic based adaptive controllers in multiple criteria decision-making tasks.
Adaptive pitch control for variable speed wind turbines
Johnson, Kathryn E.; Fingersh, Lee Jay
2012-05-08
An adaptive method for adjusting blade pitch angle, and controllers implementing such a method, for achieving higher power coefficients. Average power coefficients are determined for first and second periods of operation for the wind turbine. When the average power coefficient for the second time period is larger than for the first, a pitch increment, which may be generated based on the power coefficients, is added (or the sign is retained) to the nominal pitch angle value for the wind turbine. When the average power coefficient for the second time period is less than for the first, the pitch increment is subtracted (or the sign is changed). A control signal is generated based on the adapted pitch angle value and sent to blade pitch actuators that act to change the pitch angle of the wind turbine to the new or modified pitch angle setting, and this process is iteratively performed.
Controller-structure interaction compensation using adaptive residual mode filters
NASA Technical Reports Server (NTRS)
Davidson, Roger A.; Balas, Mark J.
1990-01-01
It is not feasible to construct controllers for large space structures or large scale systems (LSS's) which are of the same order as the structures. The complexity of the dynamics of these systems is such that full knowledge of its behavior cannot by processed by today's controller design methods. The controller for system performance of such a system is therefore based on a much smaller reduced-order model (ROM). Unfortunately, the interaction between the LSS and the ROM-based controller can produce instabilities in the closed-loop system due to the unmodeled dynamics of the LSS. Residual mode filters (RMF's) allow the systematic removal of these instabilities in a matter which does not require a redesign of the controller. In addition RMF's have a strong theoretical basis. As simple first- or second-order filters, the RMF CSI compensation technique is at once modular, simple and highly effective. RMF compensation requires knowledge of the dynamics of the system modes which resulted in the previous closed-loop instabilities (the residual modes), but this information is sometimes known imperfectly. An adaptive, self-tuning RMF design, which compensates for uncertainty in the frequency of the residual mode, has been simulated using continuous-time and discrete-time models of a flexible robot manipulator. Work has also been completed on the discrete-time experimental implementation on the Martin Marietta flexible robot manipulator experiment. This paper will present the results of that work on adaptive, self-tuning RMF's, and will clearly show the advantage of this adaptive compensation technique for controller-structure interaction (CSI) instabilities in actively-controlled LSS's.
THE EFFECTS OF BRAIN LATERALIZATION ON MOTOR CONTROL AND ADAPTATION
Mutha, Pratik K.; Haaland, Kathleen Y.; Sainburg, Robert L.
2012-01-01
Lateralization of mechanisms mediating functions such as language and perception is widely accepted as a fundamental feature of neural organization. Recent research has revealed that a similar organization exists for the control of motor actions, in that each brain hemisphere contributes unique control mechanisms to the movements of each arm. We now review current research that addresses the nature of the control mechanisms that are lateralized to each hemisphere and how they impact motor adaptation and learning. In general, the studies reviewed here suggest an enhanced role for the left hemisphere during adaptation, and the learning of new sequences and skills. We suggest that this specialization emerges from a left hemisphere specialization for predictive control – the ability to effectively plan and coordinate motor actions, possibly by optimizing certain cost functions. In contrast, right hemisphere circuits appear to be important for updating ongoing actions and stopping at a goal position, through modulation of sensorimotor stabilization mechanisms such as reflexes. We also propose that each brain hemisphere contributes its mechanism to the control of both arms. We conclude by examining the potential advantages of such a lateralized control system. PMID:23237468
Adaptive power-controllable orbital angular momentum (OAM) multicasting
Li, Shuhui; Wang, Jian
2015-01-01
We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, “up-down” power multicasting and “ladder” power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251
Adaptive power-controllable orbital angular momentum (OAM) multicasting.
Li, Shuhui; Wang, Jian
2015-01-01
We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, "up-down" power multicasting and "ladder" power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251
Adaptive control system for line-commutated inverters
NASA Technical Reports Server (NTRS)
Dolland, C. R.; Bailey, D. A. (Inventor)
1983-01-01
A control system for a permanent magnet motor driven by a multiphase line commutated inverter is provided with integration for integrating the back EMF of each phase of the motor. This is used in generating system control signals for an inverter gate logic using a sync and firing angle (alpha) control generator connected to the outputs of the integrators. A precision full wave rectifier provides a speed control feedback signal to a phase delay rectifier via a gain and loop compensation circuit and to the integrators for adaptive control of the attenuation of low frequencies by the integrators as a function of motor speed. As the motor speed increases, the attenuation of low frequency components by the integrators is increased to offset the gain of the integrators to spurious low frequencies.
Neural controller for adaptive movements with unforeseen payloads
NASA Technical Reports Server (NTRS)
Kuperstein, Michael; Wang, Jyhpyng
1990-01-01
A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated information about payload and actuator limits. Its average positioning accuracy across a large range of payloads after learning is 3 percent of the positioning range. This neural controller can be used as a basis for coordinating any number of sensory inputs with limbs of any number of joints. The feedforward nature of control allows parallel implementation in real time across multiple joints.
Passive adaptive control of chaos in synchronous reluctance motor
NASA Astrophysics Data System (ADS)
Wei, Du-Qu; Luo, Xiao-Shu
2008-01-01
The performance of synchronous reluctance motor (SynRM) degrades due to chaos when its systemic parameters fall into a certain area. To control the undesirable chaos in SynRM, a passive control law is presented in this paper, which transforms the chaotic SynRM into an equivalent passive system. It is proved that the equivalent system can be asymptotically stabilized at the set equilibrium point, namely, chaos in SynRM can be controlled. Moreover, in order to eliminate the influence of undeterministic parameters, an adaptive law is introduced into the designed controller. Computer simulation results show that the proposed controller is very effective and robust against the uncertainties in systemic parameters. The present study may help to maintain the secure operation of industrial servo drive system.
Are integral controllers adapted to the new era of ELT adaptive optics?
NASA Astrophysics Data System (ADS)
Conan, J.-M.; Raynaud, H.-F.; Kulcsár, C.; Meimon, S.
2011-09-01
With ELTs we are now entering a new era in adaptive optics developments. Meeting unprecedented level of performance with incredibly complex systems implies reconsidering AO concepts at all levels, including controller design. Concentrating mainly on temporal aspects, one may wonder if integral controllers remain an adequate solution. This question is all the more important that, with ever larger degrees of freedom, one may be tempted to discard more sophisticated approaches because they are deemed too complex to implement. The respective performance of integrator versus LQG control should therefore be carefully evaluated in the ELT context. We recall for instance the impressive correction improvement brought by such controllers for the rejection of windshake and vibration components. LQG controller significantly outperforms the integrator because its disturbance rejection transfer function closely matches the energy concentration, respectively at low temporal frequencies for windshake, and around localized resonant peaks for vibrations. The application to turbulent modes should also be investigated, especially for very low spatial frequencies now explored on the huge ELT pupil. The questions addressed here are: 1/ How do integral and LQG controllers compare in terms of performance for a given sampling frequency and noise level?; 2/ Could we relax sampling frequency with LQG control?; 3/ Does a mode to mode adaptation of temporal rejection bring significant performance improvement?; 4/ Which modes particularly benefit from this fine tuning of the rejection transfer function? Based on a simplified ELT AO configuration, and through a simple analytical formulation, performance is evaluated for several control approaches. Various assumptions concerning the perturbation parameters (seeing and outer-scale value, windshake amplitude) are considered. Bode's integral theorem allows intuitive understanding of the results. Practical implementation and computation complexity
Method and apparatus for adaptive force and position control of manipulators
NASA Technical Reports Server (NTRS)
Seraji, Homayoun (Inventor)
1989-01-01
The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.
Prediction and control of chaotic processes using nonlinear adaptive networks
Jones, R.D.; Barnes, C.W.; Flake, G.W.; Lee, K.; Lewis, P.S.; O'Rouke, M.K.; Qian, S.
1990-01-01
We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.
An experimental study of a hybrid adaptive control system
NASA Technical Reports Server (NTRS)
Lizewski, E. F.; Monopoli, R. V.
1974-01-01
A Liapunov type model reference adaptive control system with five adjustable gains is implemented using a PDP-11 digital computer and an EAI 380 analog computer. The plant controlled is a laboratory type dc servo system. It is made to follow closely a second order linear model. The experimental results demonstrate the feasibility of implementing this rather complex design using only a minicomputer and a reasonable number of operational amplifiers. Also, it points out that satisfactory performance can be achieved even when certain assumptions necessary for the theory are not satisfied.
Optimizing aircraft performance with adaptive, integrated flight/propulsion control
NASA Technical Reports Server (NTRS)
Smith, R. H.; Chisholm, J. D.; Stewart, J. F.
1991-01-01
The Performance-Seeking Control (PSC) integrated flight/propulsion adaptive control algorithm presented was developed in order to optimize total aircraft performance during steady-state engine operation. The PSC multimode algorithm minimizes fuel consumption at cruise conditions, while maximizing excess thrust during aircraft accelerations, climbs, and dashes, and simultaneously extending engine service life through reduction of fan-driving turbine inlet temperature upon engagement of the extended-life mode. The engine models incorporated by the PSC are continually upgraded, using a Kalman filter to detect anomalous operations. The PSC algorithm will be flight-demonstrated by an F-15 at NASA-Dryden.
An Adaptive Buddy Check for Observational Quality Control
NASA Technical Reports Server (NTRS)
Dee, Dick P.; Rukhovets, Leonid; Todling, Ricardo; DaSilva, Arlindo M.; Larson, Jay W.; Einaudi, Franco (Technical Monitor)
2000-01-01
An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.
Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.
Liu, Jie
2015-04-01
The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications. PMID:25749182
A Biologically Inspired Self-Adaptation of Replica Density Control
NASA Astrophysics Data System (ADS)
Izumi, Tomoko; Izumi, Taisuke; Ooshita, Fukuhito; Kakugawa, Hirotsugu; Masuzawa, Toshimitsu
Biologically-inspired approaches are one of the most promising approaches to realize highly-adaptive distributed systems. Biological systems inherently have self-* properties, such as self-stabilization, self-adaptation, self-configuration, self-optimization and self-healing. Thus, the application of biological systems into distributed systems has attracted a lot of attention recently. In this paper, we present one successful result of bio-inspired approach: we propose distributed algorithms for resource replication inspired by the single species population model. Resource replication is a crucial technique for improving system performance of distributed applications with shared resources. In systems using resource replication, generally, a larger number of replicas lead to shorter time to reach a replica of a requested resource but consume more storage of the hosts. Therefore, it is indispensable to adjust the number of replicas appropriately for the resource sharing application. This paper considers the problem for controlling the densities of replicas adaptively in dynamic networks and proposes two bio-inspired distributed algorithms for the problem. In the first algorithm, we try to control the replica density for a single resource. However, in a system where multiple resources coexist, the algorithm needs high network cost and the exact knowledge at each node about all resources in the network. In the second algorithm, the densities of all resources are controlled by the single algorithm without high network cost and the exact knowledge about all resources. This paper shows by simulations that these two algorithms realize self-adaptation of the replica density in dynamic networks.
Li, Ning; Cao, Jinde
2015-01-01
In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765
On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2011-01-01
This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.
Closed-loop adaptive control for torsional micromirrors
NASA Astrophysics Data System (ADS)
Liao, Ke-Min; Wang, Yi-Chih; Yeh, Chih-Hsien; Chen, Rongshun
2004-01-01
An adaptive control scheme to achieve accurate positioning and trajectory tracking of torsional micromirror is presented in this study. The torsional micromirror is fabricated by using surface micromachining processes, in which phosphorusdoped polysilicon is employed as the structure layer as well as the bottom electrode. Generally, every fabrication step contributes to imperfections in micromirror. The proposed adaptive self-tuning controller has advantages of on-line compensating parameter variations or model uncertainty of the torsional micromirror, resulting from fabrication imperfections that produce asymmetric structures, misalignment of actuation mechanism, and deviations of the center of mass from the geometric center. In our design, the amount of detection of differential capacitance between the left and right electrodes at the femtofarad (fF) level is utilized as feedback signals. Simulation results show that the designed controller has better transient response compared to the PID control scheme. The micromirror can follow the reference trajectory (5 kHz) with acceptable error in several microseconds, thus the convergence of the controller is confirmed. Furthermore, the unknown model parameters can be identified correctly while the so-called persistent excitation condition is satisfied.
Adaptive dynamic programming as a theory of sensorimotor control.
Jiang, Yu; Jiang, Zhong-Ping
2014-08-01
Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment. PMID:24962078
Adaptive fuzzy-neural-network control for maglev transportation system.
Wai, Rong-Jong; Lee, Jeng-Dao
2008-01-01
A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies. PMID:18269938
NASA Astrophysics Data System (ADS)
Lasaad, Sbita; Dalila, Zaltni; Naceurq, Abdelkrim Mohamed
This study demonstrates that high performance speed control can be obtained by using an adaptative sliding mode control method for a direct vector controlled Squirrel Cage Induction Motor (SCIM). In this study a new method of designing a simple and effective adaptative sliding mode rotational speed control law is developed. The design includes an accurate sliding mode flux observation from the measured stator terminals and rotor speed. The performance of the Direct Field-Orientation Control (DFOC) is ensured by online tuning based on a Model Reference Adaptative System (MRAS) rotor time constant estimator. The control strategy is derived in the sense of Lyapunov stability theory so that the stable tracking performance can be guaranteed under the occurrence of system uncertainties and external disturbances. The proposed scheme is a solution for a robust and high performance induction motor servo drives. Simulation results are provided to validate the effectiveness and robustness of the developed methodology.
The reduced order model problem in distributed parameter systems adaptive identification and control
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.
1980-01-01
The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.
NASA Astrophysics Data System (ADS)
Zhang, Jianling; An, Jinwen; Wang, Mina
2005-11-01
This paper describes the application and simulation of an adaptive fuzzy controller for a missile model. The fuzzy control system is tested using different values of fuzzy controller correctional factor on a nonlinear missile model. It is shown that the self-tuning fuzzy controller is well suited for controlling the pitch loop of the missile control system with air turbulence and parameter variety. The research shows that the Popov stability criterion could successfully guarantee the stability of the fuzzy system. It provides a good method for the design of missile control system. Simulation results suggest significant benefits from fuzzy logic in control task for missile pitch loop control.
NASA Astrophysics Data System (ADS)
Miyasato, Yoshihiko
The problem of constructing model reference adaptive H∞ control for distributed parameters systems of hyperbolic type is considered in this paper. Distributed parameters systems are infinite dimensional processes, but the proposed control scheme is constructed from finite dimensional controllers. The stabilizing control signal is added to regulate the effect of spill-over terms, and it is derived as a solution of certain H∞ control problem where spill-overs are considered as external disturbances to the process.
Direct model reference adaptive control of robotic arms
NASA Technical Reports Server (NTRS)
Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.
1993-01-01
The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.
Vipperman, J S; Clark, R L
1999-01-01
An experimental implementation of a multivariable feedback active structural acoustic control system is demonstrated on a piezostructure plate with pinned boundary conditions. Four adaptive piezoelectric sensoriactuators provide an array of truly colocated actuator/sensor pairs to be used as control transducers. Radiation filters are developed based on the self- and mutual-radiation efficiencies of the structure and are included into the performance cost of an H2 control law which minimizes total radiated sound power. In the cost function, control effort is balanced with reductions in radiated sound power. A similarity transform which produces generalized velocity states that are required as inputs to the radiation filters is presented. Up to 15 dB of attenuation in radiated sound power was observed at the resonant frequencies of the piezostructure. PMID:9921654
An adaptive spoiler to control the transonic shock
NASA Astrophysics Data System (ADS)
Bein, Th; Hanselka, H.; Breitbach, E.
2000-04-01
Market research predicts, for the aircraft industry, a large growth in the number of passengers as well as the airfreight rate with the result of this leading to increased competition for the European aircraft industry, the efficiency of new aircraft has to be improved drastically. One approach, among others, is the aerodynamic optimization of the wing. The fixed wing is designed optimally only for one flight condition. This flight condition is described by the parameters altitude, mach number and aircraft weight, all of which permanently vary during the mission of the aircraft. Therefore, the aircraft is just periodically near to the chosen design point. To compensate for this major disadvantage, an `adaptive wing' for optimal adaptation and variation of the profile geometry to the actual flight conditions will be developed. Daimler-Benz Aerospace Airbus, Daimler-Benz Research and the German Aerospace Center (DLR) are working as project partners on concepts for a variable camber and a local spoiler bump. In this paper a structural concept developed by the DLR for the adaptive spoiler will be presented. The concept is designed under the aspect of adaptive structural systems and requires a high integration of actuators, sensor and controllers in the structure. Special aspects of the design will be discussed and the first results, analytical, numerical as well as experimental, will be presented. Part of the concept design is also the development of new actuators optimized for the specific problem. A new actuator concept for the adaptive spoiler based on a cylindrical tube and activated either by pressure or multifunctional materials (e.g. shape memory alloys) will additionally be shown.
Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.
Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)
2016-01-01
Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.
Controls on Extreme Droughts and Adaptation Strategies in Semiarid Regions
NASA Astrophysics Data System (ADS)
Scanlon, B. R.; Cook, C.; Fernando, D. N.; LeBlanc, M.
2012-12-01
Increasing vulnerability to droughts with reduced per capita water storage, particularly in semiarid regions, underscores the need for predictive understanding of drought controls and development of adaptation strategies for water resources management. In this study we evaluate causes of major droughts in southwest and southcentral US (California and Texas) and southeast Australia (Murray Darling Basin). Impacts of climate cycles (ENSO, PDO, AMO, NAO, IOD) and atmospheric circulation on drought initiation and persistence are examined. Effects of drought on surface water reservoir storage, groundwater storage, irrigation, and crop production are compared. Adaptation strategies being evaluated include water transfers among sectors, particularly from irrigated agriculture to other groups, increasing storage using managed aquifer recharge, water reuse, and development of new water sources (e.g. seawater desalination). It is critical to develop a broad portfolio of water sources to increase resilience to future droughts.
Optimal control law for classical and multiconjugate adaptive optics
NASA Astrophysics Data System (ADS)
Le Roux, Brice; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Mugnier, Laurent M.; Fusco, Thierry
2004-07-01
Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems.
Optimal control law for classical and multiconjugate adaptive optics.
Le Roux, Brice; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Mugnier, Laurent M; Fusco, Thierry
2004-07-01
Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems. PMID:15260258
Adaptive control of vibrissae-like mechanical sensors
NASA Astrophysics Data System (ADS)
Behn, Carsten
2011-05-01
This paper is a contribution to the modeling and the adaptive control of bio-inspired sensors which have the animal vibrissae as a paradigm. Mice and rats employ a sophisticated tactile sensory system to explore their environment in addition to their visual and auditory sense. Vibrissae in the mystical pad (region around the mouth) are used both passively to sense environmental influences (wind, objects) and actively to detect surface and object structures. Inspired by this particular version of tactile sense we consider the following three stages of a sensory system: perception, transduction and processing of information. We model this system in combining two existing mechanical models and obtain an uncertain nonlinear control system. An applied adaptive controller implements the ability of the animals to employ their vibrissae actively as well as passively. Numerical simulations show that the developed nonlinear model compensates noise signals and reacts strongly to sudden perturbations while guaranteeing a pre-specified control objective (working in active or passive mode).
A new adaptive configuration of PID type fuzzy logic controller.
Fereidouni, Alireza; Masoum, Mohammad A S; Moghbel, Moayed
2015-05-01
In this paper, an adaptive configuration for PID type fuzzy logic controller (FLC) is proposed to improve the performances of both conventional PID (C-PID) controller and conventional PID type FLC (C-PID-FLC). The proposed configuration is called adaptive because its output scaling factors (SFs) are dynamically tuned while the controller is functioning. The initial values of SFs are calculated based on its well-tuned counterpart while the proceeding values are generated using a proposed stochastic hybrid bacterial foraging particle swarm optimization (h-BF-PSO) algorithm. The performance of the proposed configuration is evaluated through extensive simulations for different operating conditions (changes in reference, load disturbance and noise signals). The results reveal that the proposed scheme performs significantly better over the C-PID controller and the C-PID-FLC in terms of several performance indices (integral absolute error (IAE), integral-of-time-multiplied absolute error (ITAE) and integral-of-time-multiplied squared error (ITSE)), overshoot and settling time for plants with and without dead time. PMID:25530256
An adaptive identification and control scheme for large space structures
NASA Technical Reports Server (NTRS)
Carroll, J. V.
1988-01-01
A unified identification and control scheme capable of achieving space at form performance objectives under nominal or failure conditions is described. Preliminary results are also presented, showing that the methodology offers much promise for effective robust control of large space structures. The control method is a multivariable, adaptive, output predictive controller called Model Predictive Control (MPC). MPC uses a state space model and input reference trajectories of set or tracking points to adaptively generate optimum commands. For a fixed model, MPC processes commands with great efficiency, and is also highly robust. A key feature of MPC is its ability to control either nonminimum phase or open loop unstable systems. As an output controller, MPC does not explicitly require full state feedback, as do most multivariable (e.g., Linear Quadratic) methods. Its features are very useful in LSS operations, as they allow non-collocated actuators and sensors. The identification scheme is based on canonical variate analysis (CVA) of input and output data. The CVA technique is particularly suited for the measurement and identification of structural dynamic processes - that is, unsteady transient or dynamically interacting processes such as between aerodynamics and structural deformation - from short, noisy data. CVA is structured so that the identification can be done in real or near real time, using computationally stable algorithms. Modeling LSS dynamics in 1-g laboratories has always been a major impediment not only to understanding their behavior in orbit, but also to controlling it. In cases where the theoretical model is not confirmed, current methods provide few clues concerning additional dynamical relationships that are not included in the theoretical models. CVA needs no a priori model data, or structure; all statistically significant dynamical states are determined using natural, entropy-based methods. Heretofore, a major limitation in applying adaptive
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.
Space Launch System Implementation of Adaptive Augmenting Control
NASA Technical Reports Server (NTRS)
VanZwieten, Tannen S.; Wall, John H.; Orr, Jeb S.
2014-01-01
Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to robustly demonstrate stable and high performance flight. On its development path to preliminary design review (PDR), the stability of the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant dynamics. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an adaptive augmenting control (AAC) algorithm previously presented by Orr and VanZwieten, has been shown to extend the envelope of failures and flight anomalies for which the SLS control system can accommodate while maintaining a direct link to flight control stability criteria (e.g. gain & phase margin). In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the SLS digital 3-axis autopilot, including existing load-relief elements, and necessary steps for integration with the production flight software prototype have been implemented. Several updates to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.
Space Launch System Implementation of Adaptive Augmenting Control
NASA Technical Reports Server (NTRS)
Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.
2014-01-01
Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.
Exerting control and adapting to loss in amyotrophic lateral sclerosis.
Foley, Geraldine; Timonen, Virpi; Hardiman, Orla
2014-01-01
People with amyotrophic lateral sclerosis (ALS) engage with a broad range of health care services from symptom onset to end-of-life care. We undertook a grounded theory study to identify processes that underpin how and why people with ALS engage with health care services. Using theoretical sampling procedures, we sampled 34 people from the Irish ALS population-based register during September 2011 to August 2012. We conducted in-depth interviews with participants about their experiences of health care services. Our study yielded new insights into how people with ALS engage with services and adapt to loss. People with ALS live with insurmountable loss and never regain what they have already lost. Loss for people with ALS is multidimensional and includes loss of control. The experience of loss of control prompts people with ALS to search for control over health care services but exerting control in health care services can also include rendering control to service providers. People with ALS negotiate loss by exerting control over and rendering control to health care services. Our findings are important for future research that is attuned to how people with terminal illness exert control in health care services and make decisions about care in the context of mounting loss. PMID:24560231
Psychophysiological Control of Acognitive Task Using Adaptive Automation
NASA Technical Reports Server (NTRS)
Freeman, Frederick; Pope, Alan T. (Technical Monitor)
2001-01-01
The major focus of the present proposal was to examine psychophysiological variables related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding worker performance. Byrne and Parasuraman have argued for the use of psychophysiological measures in the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a cognitive vigilance task. Previous research in our laboratory, supported by NASA, has demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative than a positive, feedback condition. In addition, this condition produces less subjective workload and larger P300 event related potentials to auditory stimuli presented in a concurrent oddball task. We have also recently shown that the closed-loop system used to control the level of automation in a tracking task can also be used to control the event rate of stimuli in a vigilance monitoring task. By changing the event rate based on the subject's index of arousal, we have been able to produce improved monitoring, relative to various control groups. We have demonstrated in our initial closed-loop experiments with the the vigilance paradigm that using a negative feedback contingency (i.e. increasing event rates when the EEG index is low and decreasing event rates when
Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias
2015-01-01
The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305
Active Inference, homeostatic regulation and adaptive behavioural control
Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl
2015-01-01
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173
Fully probabilistic control design in an adaptive critic framework.
Herzallah, Randa; Kárný, Miroslav
2011-12-01
Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. PMID:21752597
Adaptive integral dynamic surface control of a hypersonic flight vehicle
NASA Astrophysics Data System (ADS)
Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick
2015-07-01
In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.
Adaptive control of vibration transmission in a strut system
NASA Astrophysics Data System (ADS)
Liao, C.-M.; Mahapatra, D. Roy; Balachandran, B.
2007-04-01
In this article, theoretical and the experimental studies are reported on the adaptive control of vibration transmission in a strut system subjected to a longitudinal pulse train excitation. In the control scheme, a magneto-strictive actuator is employed at the downstream transmission point in the secondary path. The actuator dynamics is taken into account. The system boundary parameters are first estimated off-line, and later employed to simulate the system dynamics. A Delayed-X Filtered-E spectral algorithm is proposed and implemented in real time. The underlying mechanics based filter construction allows for the time varying system dynamics to be taken into account. This work should be of interest for active control of vibration and noise transmission in helicopter gearbox support struts and other systems.
Active Inference, homeostatic regulation and adaptive behavioural control.
Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl
2015-11-01
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173
A forward method for optimal stochastic nonlinear and adaptive control
NASA Technical Reports Server (NTRS)
Bayard, David S.
1988-01-01
A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.
HIDEC adaptive engine control system flight evaluation results
NASA Technical Reports Server (NTRS)
Yonke, W. A.; Landy, R. J.; Stewart, J. F.
1987-01-01
An integrated flight propulsion control mode, the Adaptive Engine Control System (ADECS), has been developed and flight tested on an F-15 aircraft as part of the NASA Highly Integrated Digital Electronic Control program. The ADECS system realizes additional engine thrust by increasing the engine pressure ratio (EPR) at intermediate and afterburning power, with the amount of EPR uptrim modulated using a predictor scheme for angle-of-attack and sideslip angle. Substantial improvement in aircraft and engine performance was demonstrated, with a 16 percent rate of climb increase, a 14 percent reduction in time to climb, and a 15 percent reduction in time to accelerate. Significant EPR uptrim capability was found with angles-of-attack up to 20 degrees.
Adaptive-passive vibration control systems for industrial applications
NASA Astrophysics Data System (ADS)
Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.
2015-04-01
Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.
Robust time and frequency domain estimation methods in adaptive control
NASA Technical Reports Server (NTRS)
Lamaire, Richard Orville
1987-01-01
A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.
Adaptive Quality of Transmission Control in Elastic Optical Network
NASA Astrophysics Data System (ADS)
Cai, Xinran
Optical fiber communication is becoming increasingly important due to the burgeoning demand in the internet capacity. However, traditional wavelength division multiplexing (WDM) technique fails to address such demand because of its inefficient spectral utilization. As a result, elastic optical networking (EON) has been under extensive investigation recently. Such network allows sub-wavelength and super-wavelength channel accommodation, and mitigates the stranded bandwidth problem in the WDM network. In addition, elastic optical network is also able to dynamically allocate the spectral resources of the network based on channel conditions and impairments, and adaptively control the quality of transmission of a channel. This application requires two aspects to be investigated: an efficient optical performance monitoring scheme and networking control and management algorithms to reconfigure the network in a dynamic fashion. This thesis focuses on the two aspects discussed above about adaptive QoT control. We demonstrated a supervisory channel method for optical signal to noise ratio (OSNR) and chromatic dispersion (CD) monitoring. In addition, our proof-of-principle testbed experiments show successful impairment aware reconfiguration of the network with modulation format switching (MFS) only and MFS combined with lightpath rerouting (LR) for hundred-GHz QPSK superchannels undergoing time-varying OSNR impairment.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
NASA Astrophysics Data System (ADS)
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Nonlinear time-series-based adaptive control applications
NASA Technical Reports Server (NTRS)
Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.
1991-01-01
A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.
Control of commensal microbiota by the adaptive immune system.
Zhang, Husen; Luo, Xin M
2015-01-01
The symbiotic relationship between the mammalian host and gut microbes has fascinated many researchers in recent years. Use of germ-free animals has contributed to our understanding of how commensal microbes affect the host. Immunodeficiency animals lacking specific components of the mammalian immune system, on the other hand, enable studying of the reciprocal function-how the host controls which microbes to allow for symbiosis. Here we review the recent advances and discuss our perspectives of how to better understand the latter, with an emphasis on the effects of adaptive immunity on the composition and diversity of gut commensal bacteria. PMID:25901893
Control of resonant frequencies in adaptive structures by prestressing
NASA Technical Reports Server (NTRS)
Baycan, Can M.; Utku, Senol; Wada, Ben K.
1992-01-01
The natural vibration frequencies of a structure can be affected by inducing stress in the structure. The success of this kind of control of the resonant frequencies of a truss structure depends on the geometry of the structure. It is shown that in adaptive truss structures the method is effective for vibrations in less stiff directions, such as the normal direction of the plane containing all of the bars of a node, suggesting its applicability for cable, membrane, and thin plate and shell structures.
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan
2009-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.
Optimal and adaptive control in canine postural regulation.
Schuster, D; Talbott, R E
1980-07-01
For analytic purposes, dogs trained to stand quietly on an oscillating platform can be likened to a fixed-length inverted pendulum with a point mass. Describing function analysis permitted derivation of torque and error values as functions of phase and gain relative to platform movement. A phase criterion was determined for minimization of either control torque at a given error amplitude or error at a given control torque amplitude. Describing functions for dogs with and without vision approached optimal phase. Stretch reflex control involving proportional-plus-rate feedback is not sufficient to account for the approach to optimal phase. Blindfolded labyrinthectomized dogs did not exhibit optimal behavior and the phase constraint for stretch reflex control was satisfied at most frequencies. The observed behavior is best accounted for by a model involving both otolith and visual feedforward (pursuit-precognitive) control processes. Reductions in phase lag by blindfolded dogs during the first few cycles of platform motion provide evidence of adaptive control. PMID:7396044
Efficient community-based control strategies in adaptive networks
NASA Astrophysics Data System (ADS)
Yang, Hui; Tang, Ming; Zhang, Hai-Feng
2012-12-01
Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible-infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible-infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans.
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. PMID:26899554
Pixelized Device Control Actuators for Large Adaptive Optics
NASA Technical Reports Server (NTRS)
Knowles, Gareth J.; Bird, Ross W.; Shea, Brian; Chen, Peter
2009-01-01
A fully integrated, compact, adaptive space optic mirror assembly has been developed, incorporating new advances in ultralight, high-performance composite mirrors. The composite mirrors use Q-switch matrix architecture-based pixelized control (PMN-PT) actuators, which achieve high-performance, large adaptive optic capability, while reducing the weight of present adaptive optic systems. The self-contained, fully assembled, 11x11x4-in. (approx.= 28x28x10-cm) unit integrates a very-high-performance 8-in. (approx.=20-cm) optic, and has 8-kHz true bandwidth. The assembled unit weighs less than 15 pounds (=6.8 kg), including all mechanical assemblies, power electronics, control electronics, drive electronics, face sheet, wiring, and cabling. It requires just three wires to be attached (power, ground, and signal) for full-function systems integration, and uses a steel-frame and epoxied electronics. The three main innovations are: 1. Ultralightweight composite optics: A new replication method for fabrication of very thin composite 20-cm-diameter laminate face sheets with good as-fabricated optical figure was developed. The approach is a new mandrel resin surface deposition onto previously fabricated thin composite laminates. 2. Matrix (regenerative) power topology: Waveform correction can be achieved across an entire face sheet at 6 kHz, even for large actuator counts. In practice, it was found to be better to develop a quadrant drive, that is, four quadrants of 169 actuators behind the face sheet. Each quadrant has a single, small, regenerative power supply driving all 169 actuators at 8 kHz in effective parallel. 3. Q-switch drive architecture: The Q-switch innovation is at the heart of the matrix architecture, and allows for a very fast current draw into a desired actuator element in 120 counts of a MHz clock without any actuator coupling.
Adaptive plasticity in vestibular influences on cardiovascular control
NASA Technical Reports Server (NTRS)
Yates, B. J.; Holmes, M. J.; Jian, B. J.
2000-01-01
Data collected in both human subjects and animal models indicate that the vestibular system influences the control of blood pressure. In animals, peripheral vestibular lesions diminish the capacity to rapidly and accurately make cardiovascular adjustments to changes in posture. Thus, one role of vestibulo-cardiovascular influences is to elicit changes in blood distribution in the body so that stable blood pressure is maintained during movement. However, deficits in correcting blood pressure following vestibular lesions diminish over time, and are less severe when non-labyrinthine sensory cues regarding body position in space are provided. These observations show that pathways that mediate vestibulo-sympathetic reflexes can be subject to plastic changes. This review considers the adaptive plasticity in cardiovascular responses elicited by the central vestibular system. Recent data indicate that the posterior cerebellar vermis may play an important role in adaptation of these responses, such that ablation of the posterior vermis impairs recovery of orthostatic tolerance following subsequent vestibular lesions. Furthermore, recent experiments suggest that non-labyrinthine inputs to the central vestibular system may be important in controlling blood pressure during movement, particularly following vestibular dysfunction. A number of sensory inputs appear to be integrated to produce cardiovascular adjustments during changes in posture. Although loss of any one of these inputs does not induce lability in blood pressure, it is likely that maximal blood pressure stability is achieved by the integration of a variety of sensory cues signaling body position in space.
Neural Controller For Adaptive Sensory-Motor Coordination
NASA Astrophysics Data System (ADS)
Kuperstein, Michael; Rubinstein, Jorge
1989-03-01
We present a theory and prototype of a neural controller called INFANT that learns sensory-motor coordination from its own experience. INFANT adapts to unforeseen changes in the geometry of the physical motor system and to the location, orientation, shape and size of objects. It can learn to accurately grasp an elongated object without any information about the geometry of the physical sensory-motor system. This new neural controller relies on the self-consistency between sensory and motor signals to achieve unsupervised learning. It is designed to be generalized for coordinating any number of sensory inputs with limbs of any number of joints. INFANT is implemented with an image processor, stereo cameras and a five degree-of freedom robot arm. Its average grasping accuracy after learning is 3% of the arm's length in position and 6 degrees in orientation.
Kalman filtering to suppress spurious signals in Adaptive Optics control
Poyneer, L; Veran, J P
2010-03-29
In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.
On-line, adaptive state estimator for active noise control
NASA Technical Reports Server (NTRS)
Lim, Tae W.
1994-01-01
Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control
Development of adaptive sensorimotor control in infant sitting posture.
Chen, Li-Chiou; Jeka, John; Clark, Jane E
2016-03-01
A reliable and adaptive relationship between action and perception is necessary for postural control. Our understanding of how this adaptive sensorimotor control develops during infancy is very limited. This study examines the dynamic visual-postural relationship during early development. Twenty healthy infants were divided into 4 developmental groups (each n=5): sitting onset, standing alone, walking onset, and 1-year post-walking. During the experiment, the infant sat independently in a virtual moving-room in which anterior-posterior oscillations of visual motion were presented using a sum-of-sines technique with five input frequencies (from 0.12 to 1.24Hz). Infants were tested in five conditions that varied in the amplitude of visual motion (from 0 to 8.64cm). Gain and phase responses of infants' postural sway were analyzed. Our results showed that infants, from a few months post-sitting to 1 year post-walking, were able to control their sitting posture in response to various frequency and amplitude properties of the visual motion. Infants showed an adult-like inverted-U pattern for the frequency response to visual inputs with the highest gain at 0.52 and 0.76Hz. As the visual motion amplitude increased, the gain response decreased. For the phase response, an adult-like frequency-dependent pattern was observed in all amplitude conditions for the experienced walkers. Newly sitting infants, however, showed variable postural behavior and did not systemically respond to the visual stimulus. Our results suggest that visual-postural entrainment and sensory re-weighting are fundamental processes that are present after a few months post sitting. Sensorimotor refinement during early postural development may result from the interactions of improved self-motion control and enhanced perceptual abilities. PMID:26979899
Model adaptation in a central controller for a sewer system
NASA Astrophysics Data System (ADS)
van Nooijen, Ronald; Kolechkina, Alla; Mol, Bart
2013-04-01
For small sewer systems that combine foul water and storm water sewer functions in flat terrain, central control of the sewer system may have problems during dry weather. These systems are a combination of local gravity flow networks connected by pumps. Under those conditions the level in the wet well (local storage at the pumping station) should be kept below the entrance pipe but above the top of the intake of the pump. The pumps are dimensioned to cope with the combined flow of foul water and precipitation run off so their capacity is relatively large when compared wityh the volume available in the wet well. Under local control this is not a major problem because the effective controller time step is very short. For central control the control time step can become a problem. Especially when there is uncertainty about the relation between level and volume in the wet well. In this paper we describe a way to dynamically adapt the level to volume relation based on dry weather behaviour. This is important because a better estimate of this volume will reduce the number of on/off cycles for the pumps. It will also allow detection and correction for changes in pump performance due to aging.
Adaptive active control of periodic vibration using maglev actuators
NASA Astrophysics Data System (ADS)
An, Fengyan; Sun, Hongling; Li, Xiaodong
2012-04-01
In this paper, active control of periodic vibration is implemented using maglev actuators which exhibit inherent nonlinear behaviors. A multi-channel feedforward control algorithm is proposed to solve these nonlinear problems, in which maglev actuators are treated as single-input-single-output systems with unknown time-varying nonlinearities. A radial basis function network is used by the algorithm as its controller, whose parameters are adapted only with the model of the linear system in the secondary path. Compared with the strategies in the conventional magnetic-levitation system control as well as nonlinear active noise/vibration control, the proposed algorithm has the advantage that the nonlinear modeling procedure of maglev actuators and the usage of displacement sensors could be both avoided. Numerical simulations and real-time experiments are carried out based on a multiple-degree-of-freedom vibration isolation system. The results show that the proposed algorithm not only could efficiently compensate for the actuators' time-varying nonlinearities, but also has the ability to greatly attenuate the energy of periodic vibration.
Adaptive bridge control strategy for opinion evolution on social networks
NASA Astrophysics Data System (ADS)
Qian, Cheng; Cao, Jinde; Lu, Jianquan; Kurths, Jürgen
2011-06-01
In this paper, we present an efficient opinion control strategy for complex networks, in particular, for social networks. The proposed adaptive bridge control (ABC) strategy calls for controlling a special kind of nodes named bridge and requires no knowledge of the node degrees or any other global or local knowledge, which are necessary for some other immunization strategies including targeted immunization and acquaintance immunization. We study the efficiency of the proposed ABC strategy on random networks, small-world networks, scale-free networks, and the random networks adjusted by the edge exchanging method. Our results show that the proposed ABC strategy is efficient for all of these four kinds of networks. Through an adjusting clustering coefficient by the edge exchanging method, it is found out that the efficiency of our ABC strategy is closely related with the clustering coefficient. The main contributions of this paper can be listed as follows: (1) A new high-order social network is proposed to describe opinion dynamic. (2) An algorithm, which does not require the knowledge of the nodes' degree and other global/local network structure information, is proposed to control the "bridges" more accurately and further control the opinion dynamics of the social networks. The efficiency of our ABC strategy is illustrated by numerical examples. (3) The numerical results indicate that our ABC strategy is more efficient for networks with higher clustering coefficient.
Dynamic modeling and adaptive control for space stations
NASA Technical Reports Server (NTRS)
Ih, C. H. C.; Wang, S. J.
1985-01-01
Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.
Real-Time Feedback Control of Flow-Induced Cavity Tones. Part 2; Adaptive Control
NASA Technical Reports Server (NTRS)
Kegerise, M. A.; Cabell, R. H.; Cattafesta, L. N., III
2006-01-01
An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. Past input-output data and an estimate of the open-loop pulse response sequence are all that is needed to implement the algorithm for application at fixed Mach numbers. Transient measurements made during controller adaptation revealed that the controller coefficients converged to a steady state in the mean, and this implies that adaptation can be turned off at some point with no degradation in control performance. When converged, the control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. However, as in the case of fixed-gain GPC, the adaptive GPC performance was limited by spillover in sidebands around the suppressed Rossiter modes. The algorithm was also able to maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Beyond this range, stable operation of the control algorithm was not possible due to the fixed plant model in the algorithm.
Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control
NASA Technical Reports Server (NTRS)
Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)
2015-01-01
Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.
Alavandar, Srinivasan; Nigam, M J
2009-10-01
Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. In this paper, some new hybrid adaptive neuro-fuzzy control algorithms (ANFIS) have been proposed for manipulator control with uncertainties. These hybrid controllers consist of adaptive neuro-fuzzy controllers and conventional controllers. The outputs of these controllers are applied to produce the final actuation signal based on current position and velocity errors. Numerical simulation using the dynamic model of six DOF puma robot arm with uncertainties shows the effectiveness of the approach in trajectory tracking problems. Performance indices of RMS error, maximum error are used for comparison. It is observed that the hybrid adaptive neuro-fuzzy controllers perform better than only conventional/adaptive controllers and in particular hybrid controller structure consisting of adaptive neuro-fuzzy controller and critically damped inverse dynamics controller. PMID:19523623
L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition
NASA Technical Reports Server (NTRS)
Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu
2010-01-01
Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.
Optimal Control Modification Adaptive Law for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
Experimental study on direct adaptive control of a PUMA 560 industrial robot
NASA Technical Reports Server (NTRS)
Seraji, H.; Lee, T.; Delpech, M.
1990-01-01
The implementation and experimental validation of a direct adaptive control scheme on a PUMA 560 industrial robot is discussed. The design theory for direct adaptive control of manipulators is outlined and the test facility and software are described. Results are presented from the experiments on the simultaneous control of all of the six joint angles and control of the end-effector position and orientation of the robot. Also, the possible applications of the direct adaptive control scheme are considered.
Adaptive source rate control for wireless video conferencing
NASA Astrophysics Data System (ADS)
Liu, Hang; El Zarki, Magda
1997-12-01
Hybrid ARQ schemes can yield much better throughput and reliability than static FEC schemes for the transmission of data over time-varying wireless channels. However these schemes result in higher delay. They adapt to the varying channel conditions by retransmitting erroneous packets, this results in variable effective data rates for current PCS networks because the channel bandwidth is constant. Hybrid ARQ schemes are currently being proposed as the error control schemes for real-time video transmission. The standardization process is on-going in ITU, MPEG-4 and wireless ATM forum. The important issue is how to ensure low delay while taking advantage of the high throughput and reliability that these schemes provide for. In this paper we propose an adaptive source rate control (ASRC) protocol which can work together with the hybrid ARQ error control schemes to achieve efficient transmission of real-time video with low delay and high reliability. The ASRC scheme adjusts the source rate based on the channel conditions, the transport buffer occupancy and the delay constraints. It optimizes the video quality by dynamically changing both the number of the forced update (intracoded) macroblocks and the quantization scale used in a frame. The number of the forced update macroblocks used in a frame is first adjusted according to the allocated source rate. This reduces the fluctuation of the quantization scale with the change in the channel conditions during encoding so that the uniformity of the video quality is improved. The simulation results show that the proposed ASRC protocol performs very well for both slow fading and fast fading channels.
A self-adaptive feedforward rf control system for linacs
NASA Astrophysics Data System (ADS)
Zhang, Renshan; Ben-Zvi, Ilan; Xie, Jialin
1993-01-01
The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6°. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±0.5% in amplitude and simultaneously to ±1° in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±0.2%.
Adaptive controller for volumetric display of neuroimaging studies
NASA Astrophysics Data System (ADS)
Bleiberg, Ben; Senseney, Justin; Caban, Jesus
2014-03-01
Volumetric display of medical images is an increasingly relevant method for examining an imaging acquisition as the prevalence of thin-slice imaging increases in clinical studies. Current mouse and keyboard implementations for volumetric control provide neither the sensitivity nor specificity required to manipulate a volumetric display for efficient reading in a clinical setting. Solutions to efficient volumetric manipulation provide more sensitivity by removing the binary nature of actions controlled by keyboard clicks, but specificity is lost because a single action may change display in several directions. When specificity is then further addressed by re-implementing hardware binary functions through the introduction of mode control, the result is a cumbersome interface that fails to achieve the revolutionary benefit required for adoption of a new technology. We address the specificity versus sensitivity problem of volumetric interfaces by providing adaptive positional awareness to the volumetric control device by manipulating communication between hardware driver and existing software methods for volumetric display of medical images. This creates a tethered effect for volumetric display, providing a smooth interface that improves on existing hardware approaches to volumetric scene manipulation.
Flight Validation of a Metrics Driven L(sub 1) Adaptive Control
NASA Technical Reports Server (NTRS)
Dobrokhodov, Vladimir; Kitsios, Ioannis; Kaminer, Isaac; Jones, Kevin D.; Xargay, Enric; Hovakimyan, Naira; Cao, Chengyu; Lizarraga, Mariano I.; Gregory, Irene M.
2008-01-01
The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf AP with and without adaptive augmentation to recover from control surface failures.
Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.
Gordon, Keith E; Kinnaird, Catherine R; Ferris, Daniel P
2013-04-01
Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to "fight" the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations. PMID:23307949
Adaptive glide slope control for parafoil and payload aircraft
NASA Astrophysics Data System (ADS)
Ward, Michael
Airdrop systems provide a unique capability of delivering large payloads to undeveloped and inaccessible locations. Traditionally, these systems have been unguided, requiring large landing zones and drops from low altitude. The invention of the steerable, gliding, ram-air parafoil enabled the possibility of precision aerial payload delivery. In practice, the gliding ability of the ram-air parafoil can actually create major problems for airdrop systems by making them more susceptible to winds and allowing them to achieve far greater miss distances than were previously possible. Research and development work on guided airdrop systems has focused primarily on evolutionary improvements to the guidance algorithm, while the navigation and control algorithms have changed little since the initial autnomous systems were developed. Furthermore, the control mechanisms have not changed since the invention of the ram-air canopy in the 1960’s. The primary contributions of this dissertation are: (1) the development of a reliable and robust method to identify a flight dynamic model for a parafoil and payload aircraft using minimal sensor data; (2) the first demonstration in flight test of the ability to achieve large changes in glide slope over ground using coupled incidence angle variation and trailing edge brake deflection; (3) the first development of a control law to implement glide slope control on an autonomous system; (4) the first flight tests of autonomous landing with a glide slope control mechanism demonstrating an improvement in landing accuracy by a factor of 2 or more in especially windy conditions, and (5) the first demonstrations in both simulation and flight test of the ability to perform in-flight system identification to adapt the internal control mappings to flight data and provide dramatic improvements in landing accuracy when there is a significant discrepancy between the assumed and actual flight characteristics.
Method and apparatus for adaptive force and position control of manipulators
NASA Technical Reports Server (NTRS)
Seraji, Homayoun (Inventor)
1995-01-01
The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.
Materials for adaptive structural acoustic control, volume 1
NASA Astrophysics Data System (ADS)
Cross, L. E.
1993-04-01
This report documents work carried out in the Materials Research Laboratory of the Pennsylvania State University over the first year of a new ONR sponsored University Research Initiative (URI) entitled Materials for Adaptive Structural Acoustic Control. For this report the activities have been grouped under the following topic headings: (1) General Summary Papers; (2) Materials Studies; (3) Composite Sensors; (4) Actuator Studies; (5) Integration Issues; (6) Processing Studies; and (7) Thin Film Ferroelectrics. In material studies important advances have been made in the understanding of the evaluation of relaxor behavior in the PLZT's and of the order disorder behavior in lead scandium tantalate:lead titanate solid solutions and of the Morphotropic Phase Boundary in this system.
Mekong Delta at the crossroads: more control or adaptation?
Käkönen, Mira
2008-05-01
Development in the Mekong Delta of Vietnam has been very dynamic in the recent past, and currently it stands at an interesting crossroads. On one hand, agricultural production has developed successfully, and economic growth has been very rapid, but on the other hand, intensifying agriculture and large-scale water-control structures have challenged the environmental sustainability and social equity. The development plans have included a strong belief in the human mastery over the nature and waters of the Mekong Delta. In many cases, water resources planners have underestimated the complexity and integrated nature of the ecology and livelihoods of the Mekong Delta. This article examines cases where development efforts, while successful in some dimensions, have also contributed to create new risks for, especially, the poorest groups. The current situation calls for a more sustainable future route that would require examination of more adaptive measures in relation to the changing water flows of the Mekong River. PMID:18595276
Adaptive MFR parameter control: fixed vs. variable probabilities of detection
NASA Astrophysics Data System (ADS)
Boers, Yvo; Driessen, Hans; Zwaga, Jitse
2005-09-01
In this paper an efficient adaptive parameter control scheme for Multi Function Radar (MFR) is used. This scheme has been introduced in.5 The scheme has been designed in such a way that it meets constraints on specific quantities that are relevant for target tracking while minimizing the energy spent. It is shown here, that this optimal scheme leads to a considerable variation of the realized detection probability, even within a single scenario. We also show that constraining or fixing the probability of detection to a certain predefined value leads to a considerable increase in the energy spent on the target. This holds even when one optimizes the fixed probability of detection. The bottom line message is that the detection probability is not a design parameter by itself, but merely the product of an optimal schedule.
Adaptive sliding mode control - convergence and gain boundedness revisited
NASA Astrophysics Data System (ADS)
Zhu, Jiang; Khayati, Karim
2016-04-01
This paper reviews the main adaptive sliding mode controller (ASMC) designs for nonlinear systems with finite uncertainties of unknown bounds. Different statements of convergence referring to uniformly ultimate boundedness (UUB), asymptotic convergence (AC) and finite-time convergence (FTC) for ASMC shown in recent papers are analysed. Weaknesses and incomplete proofs apropos FTC are pointed out. Thereafter, a new approach is proposed to successfully demonstrate FTC of the so-called sliding variable. We identify a compensating phase and a reaching phase during the ASMC process. A new explicit form for estimating the upper-bound reaching time is provided for any bounded perturbation. An amended form of the real ASMC is recalled showing improved accuracy and chattering reduction. Finally, numerical and experimental applications are performed to convey the discussed results.
An integrated architecture of adaptive neural network control for dynamic systems
Ke, Liu; Tokar, R.; Mcvey, B.
1994-07-01
In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.
Adaptive Postural Control for Joint Immobilization during Multitask Performance
Hsu, Wei-Li
2014-01-01
Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21–29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements. PMID:25329477
Adaptive Suction and Blowing for Twin-Tail Buffet Control
NASA Technical Reports Server (NTRS)
Kandil, Osama A.; Yang, Zhi
1999-01-01
Adaptive active flow control for twin-tail buffet alleviation is investigated. The concept behind this technique is to place control ports on the tail outer and inner surfaces with flow suction or blowing applied through these ports in order to minimize the pressure difference across the tail. The suction or blowing volume flow rate from each port is proportional to the pressure difference across the tail at this location. A parametric study of the effects of the number and location of these ports on the buffet response is carried out. The computational model consists of a sharp-edged delta wing of aspect ratio one and swept-back flexible twin tail with taper ratio of 0.23. This complex multidisciplinary problem is solved sequentially using three sets of equations for the fluid flow, aeroelastic response and grid deformation, using a dynamic multi-block grid structure. The computational model is pitched at 30 deg angle of attack. The freestream Mach number and Reynolds number are 0.3 and 1.25 million, respectively. The model is investigated for the inboard position of the twin tails, which corresponds to a separation distance between the twin tails of 33% of the wing span. Comparison of the time history and power spectral density responses of the tails for various distributions of the control ports are presented and discussed.
Materials for adaptive structural acoustic control, volume 2
NASA Astrophysics Data System (ADS)
Cross, L. E.
1993-04-01
This report documents work carried out in the Materials Research Laboratory of the Pennsylvania State University over the first year of a new ONR sponsored University Research Initiative (URI) entitled Materials for Adaptive Structural Acoustic Control. For this report the activities have been grouped under the following topic headings: (1) General Summary Papers; (2) Materials Studies; (3) Composite Sensors; (4) Actuator Studies; (5) Integration Issues; (6) Processing Studies; (7) Thin Film Ferroelectrics. In material studies important advances have been made in the understanding of the evaluation of relaxor behavior in the PLZT's and of the order disorder behavior in lead scandium tantalate:lead titanate solid solutions and of the Morphotropic Phase Boundary in this system. For both composite sensors and actuators we have continued to explore and exploit the remarkable versatility of the flextensional moonie type structure. Finite element (FEA) calculations have given a clear picture of the lower order resonant modes and permitted the evaluation of various end cap metals, cap geometries and load conditions. In actuator studies multilayer structures have been combined with flextensional moonie endcaps to yield high displacement (50 micrometers) compact structures. Electrically controlled shape memory has been demonstrated in lead zirconate stannate titanate compositions, and used for controlling a simple latching relay.
Materials for adaptive structural acoustic control, volume 3
NASA Astrophysics Data System (ADS)
Cross, L. E.
1993-04-01
This report documents work carried out in the Materials Research Laboratory of the Pennsylvania State University over the first year of a new ONR sponsored University Research Initiative (URI) entitled Materials for Adaptive Structural Acoustic Control. For this report the activities have been grouped under the following topic headings: (1) General Summary Papers; (2) Materials Studies; (3) Composite Sensors; (4) Actuator Studies; (5) Integration Issues; (6) Processing Studies; and (7) Thin Film Ferroelectrics. In material studies important advances have been made in the understanding of the evaluation of relaxor behavior in the PLZT's and of the order-disorder behavior in lead scandium tantalate:lead titanate solid solutions and of the Morphotropic Phase Boundary in this system. For both composite sensors and actuators, we have continued to explore and exploit the remarkable versatility of the flextensional moonie type structure. Finite element (FEA) calculations have given a clear picture of the lower order resonant modes and permitted the evaluation of various end cap metals, cap geometries, and load conditions. In actuator studies multilayer structures have been combined with flextensional moonie endcaps to yield high displacement (50 micrometers) compact structures. Electrically controlled shape memory has been demonstrated in lead zirconate stannate titanate compositions, and used for controlling a simple latching relay.
Rear-heavy car control by adaptive linear optimal preview
NASA Astrophysics Data System (ADS)
Thommyppillai, M.; Evangelou, S.; Sharp, R. S.
2010-05-01
Adaptive linear optimal preview control theory is applied to a simple but non-linear car model, with parameters chosen to make the rear axle saturate first in any quasi-steady manoeuvre. The tendency of such a car to spin above a critical speed, which is a function of its running state, causes control to be especially difficult when operating near to the limit of the rear-axle force system. As in previous work, trim states and optimal gains are computed off-line for a given speed and a full range of lateral accelerations. Gain-scheduling with interpolation over trims and gain sets is used to keep the control appropriate to the running conditions, as they change. Simulations of manoeuvres are used to test and demonstrate the system capability. It is shown that utilising the rear-axle lateral-slip ratio as the scheduling variable, in the case of this rear-heavy car, gives excellent tracking, even when the tyres are run close to full saturation. It is implied by this and previous work that the general case can be treated effectively by monitoring both front- and rear-axle slips and scheduling on a worst-case basis.
System identification, adaptive control and formation driving of farm tractors
NASA Astrophysics Data System (ADS)
Rekow, Andrew Karl Wilhelm
Great increases in agricultural productivity and profitability can be gained by increasing the navigational control accuracy of a farm tractor. To maximize accuracy in the presence of environmental uncertainties, a novel technique for on-line parameter identification has been developed. This method combines the Extended Kalman Filter (EKF) and the Least Mean Square (LMS) algorithms and is used to identify key parameters which describe the dynamics of a farm tractor. This algorithm provides a 15:1 improvement in computational efficiency over the traditional EKF, while offering comparable convergence rates and noise rejection properties. Experimental data on a full-sized John Deere tractor shows a 25 percent improvement in lateral accuracy when using then adaptive controller versus a fixed controller over identical trajectories. In addition to parameter identification, farmers require formation driving capability for routine operations. Multiple farm vehicles work cooperatively together to accomplish a common goal. Several formation driving algorithms were developed for these varying requirements. An experimental implementation of a fully autonomous farm vehicle following a human operated lead vehicle demonstrated an accuracy of 10 centimeters in the in-track direction and 10 centimeters in the cross track direction.
STDP with adaptive synaptic delay for robot navigation control
NASA Astrophysics Data System (ADS)
Arena, Paolo; Patané, Luca; Distefano, Francesco; Bucolo, Sebastiano; Aiello, Orazio
2007-05-01
In this work a biologically inspired network of spiking neurons is used for robot navigation control. The two tasks taken into account are obstacle avoidance and landmark-based navigation. The system learns the correlation among unconditioned stimuli (pre-wired sensors) and conditioned stimuli (high level sensors) through Spike Timing Dependent Plasticity (STDP). In order to improve the robot behaviours not only the synaptic weight but also the synaptic delay is subject to learning. Modulating the synaptic delay the robot is able to store the landmark position, like in a short time memory, and to use this information to smooth the turning actions prolonging the landmark effects also when it is no more visible. Simulations are carried out in a dynamic simulation environment and the robotic system considered is a cockroach-inspired hexapod robot. The locomotion signals are generated by a Central Pattern Generator and the spiking network is devoted to control the heading of the robot acting on the amplitude of the leg steps. Several scenarios have been proposed, for instance a T-shaped labyrinth, used in laboratory experiments with mice to demonstrate classical and operant conditioning, has been considered. Finally the proposed adaptive navigation control structure can be extended in a modular way to include other features detected by new sensors included in the correlation-based learning process.
Interior Noise Reduction by Adaptive Feedback Vibration Control
NASA Technical Reports Server (NTRS)
Lim, Tae W.
1998-01-01
The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study
Exposure Control Using Adaptive Multi-Stage Item Bundles.
ERIC Educational Resources Information Center
Luecht, Richard M.
This paper presents a multistage adaptive testing test development paradigm that promises to handle content balancing and other test development needs, psychometric reliability concerns, and item exposure. The bundled multistage adaptive testing (BMAT) framework is a modification of the computer-adaptive sequential testing framework introduced by…
NASA Astrophysics Data System (ADS)
Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing
2015-08-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).
NASA Astrophysics Data System (ADS)
Miyasato, Yoshihiko
The problem of constructing model reference adaptive H∞ control for a class of mixed parameter systems is considered in this manuscript. Mixed parameter systems are complex processes composed of distributed parameter systems (infinite dimensional systems) and lumped parameter systems (finite dimensional systems). Owing to infinite dimensional modes of distributed parameter systems, control of those complex systems via finite dimensional compensators, is a difficult but important problem from both theoretical and practical viewpoints. A stabilizing control signal is added to regulate the effect of infinite dimensional modes, and it is derived as a solution of certain H∞ control problem where the effect of infinite dimensional modes are considered as external disturbances to the process.
MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.
Najjar-Khodabakhsh, Abbas; Soltani, Jafar
2016-03-01
In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. PMID:26830002
Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Rohrs, C. E.
1982-01-01
Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.
An Adaptable Power System with Software Control Algorithm
NASA Technical Reports Server (NTRS)
Castell, Karen; Bay, Mike; Hernandez-Pellerano, Amri; Ha, Kong
1998-01-01
A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system
Yang, Cheng-Hsiung; Wu, Cheng-Lin
2014-01-01
An adaptive control scheme is developed to study the generalized adaptive chaos synchronization with uncertain chaotic parameters behavior between two identical chaotic dynamic systems. This generalized adaptive chaos synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the adaptive controller with its update laws of uncertain chaotic parameters is shown. The generalized adaptive synchronization with uncertain parameters between two identical new Lorenz-Stenflo systems is taken as three examples to show the effectiveness of the proposed method. The numerical simulations are shown to verify the results. PMID:25295292
Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network
Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A.; Carrillo, Richard R.; Luque, Niceto R.; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio
2014-01-01
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365
Adaptive robotic control driven by a versatile spiking cerebellar network.
Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio
2014-01-01
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365
FPGA-accelerated adaptive optics wavefront control part II
NASA Astrophysics Data System (ADS)
Mauch, S.; Barth, A.; Reger, J.; Reinlein, C.; Appelfelder, M.; Beckert, E.
2015-03-01
We present progressive work that is based on our recently developed rapid control prototyping system (RCP), designed for the implementation of high-performance adaptive optical control algorithms using a continuous de-formable mirror (DM). The RCP system, presented in 2014, is resorting to a Xilinx Kintex-7 Field Programmable Gate Array (FPGA), placed on a self-developed PCIe card, and installed on a high-performance computer that runs a hard real-time Linux operating system. For this purpose, algorithms for the eﬃcient evaluation of data from a Shack-Hartmann wavefront sensor (SHWFS) on an FPGA have been developed. The corresponding analog input and output cards are designed for exploiting the maximum possible performance while not being constrained to a specific DM and control algorithm due to the RCP approach. In this second part of our contribution, we focus on recent results that we achieved with this novel experimental setup. By presenting results which are far superior to the former ones, we further justify the deployment of the RCP system and its required time and resources. We conducted various experiments for revealing the effective performance, i.e. the maximum manageable complexity in the controller design that may be achieved in real-time without performance losses. A detailed analysis of the hidden latencies is carried out, showing that these latencies have been drastically reduced. In addition, a series of concepts relating the evaluation of the wavefront as well as designing and synthesizing a wavefront are thoroughly investigated with the goal to overcome some of the prevalent limitations. Furthermore, principal results regarding the closed-loop performance of the low-speed dynamics of the integrated heater in a DM concept are illustrated in detail; to be combined with the piezo-electric high-speed actuators in the next step
Real-time control of geometry and stiffness in adaptive structures
NASA Technical Reports Server (NTRS)
Ramesh, A. V.; Utku, S.; Wada, B. K.
1991-01-01
The basic theory is presented for the geometry, stiffness, and damping control of adaptive structures, with emphasis on adaptive truss structures. Necessary and sufficient conditions are given for stress-free geometry control in statically determinate and indeterminate adaptive discrete structures. Two criteria for selecting the controls are proposed, and their use in real-time control is illustrated by numerical simulation results. It is shown that the stiffness and damping control of adaptive truss structures for vibration suppression is possible by elongation and elongation rate dependent feedback forces from the active elements.
L(sub 1) Adaptive Control Design for NASA AirSTAR Flight Test Vehicle
NASA Technical Reports Server (NTRS)
Gregory, Irene M.; Cao, Chengyu; Hovakimyan, Naira; Zou, Xiaotian
2009-01-01
In this paper we present a new L(sub 1) adaptive control architecture that directly compensates for matched as well as unmatched system uncertainty. To evaluate the L(sub 1) adaptive controller, we take advantage of the flexible research environment with rapid prototyping and testing of control laws in the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. We apply the L(sub 1) adaptive control laws to the subscale turbine powered Generic Transport Model. The presented results are from a full nonlinear simulation of the Generic Transport Model and some preliminary pilot evaluations of the L(sub 1) adaptive control law.
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
NASA Astrophysics Data System (ADS)
Engel, E.; Kovalev, I. V.; Kobezhicov, V.
2015-10-01
This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.
Adaptive control of an active seat for occupant vibration reduction
NASA Astrophysics Data System (ADS)
Gan, Zengkang; Hillis, Andrew J.; Darling, Jocelyn
2015-08-01
The harmful effects on human performance and health caused by unwanted vibration from vehicle seats are of increasing concern. This paper presents an active seat system to reduce the vibration level transmitted to the seat pan and the occupants' body under low frequency periodic excitation. Firstly, the detail of the mechanical structure is given and the active seat dynamics without external load are characterized by vibration transmissibility and frequency responses under different excitation forces. Owing the nonlinear and time-varying behaviour of the proposed system, a Filtered-x least-mean-square (FXLMS) adaptive control algorithm with on-line Fast-block LMS (FBLMS) identification process is employed to manage the system operation for high vibration cancellation performance. The effectiveness of the active seat system is assessed through real-time experimental tests using different excitation profiles. The system identification results show that an accurate estimation of the secondary path is achieved by using the FBLMS on-line technique. Substantial reduction is found for cancelling periodic vibration containing single and multiple frequencies. Additionally, the robustness and stability of the control system are validated through transient switching frequency tests.
Method for removing tilt control in adaptive optics systems
Salmon, J.T.
1998-04-28
A new adaptive optics system and method of operation are disclosed, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G{prime} = (I{minus}X(X{sup T} X){sup {minus}1}X{sup T})G(I{minus}A). 3 figs.
Method for removing tilt control in adaptive optics systems
Salmon, Joseph Thaddeus
1998-01-01
A new adaptive optics system and method of operation, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G'=(I-X(X.sup.T X).sup.-1 X.sup.T)G(I-A)
NASA Astrophysics Data System (ADS)
Wu, Zhenhui; Dong, Chaoyang
2006-11-01
Because of nonlinearity and strong coupling of reaction-jet and aerodynamics compound control missile, a missile autopilot design method based on adaptive fuzzy sliding mode control (AFSMC) is proposed in this paper. The universal approximation ability of adaptive fuzzy system is used to approximate the nonlinear function in missile dynamics equation during the flight of high angle of attack. And because the sliding mode control is robustness to external disturbance strongly, the sliding mode surface of the error system is constructed to overcome the influence of approximation error and external disturbance so that the actual overload can track the maneuvering command with high precision. Simulation results show that the missile autopilot designed in this paper not only can track large overload command with higher precision than traditional method, but also is robust to model uncertainty and external disturbance strongly.
Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2016-01-01
This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of N subsystems in pure feedback structure and the interconnection terms are contained in every equation of each subsystem. Moreover, the studied systems consider the effects of Prandtl-Ishlinskii (PI) hysteresis model. It is for the first time to study the control problem for such a class of systems. In addition, the proposed scheme removes an important assumption imposed on the previous works that the bounds of the parameters in PI hysteresis are known. The radial basis functions neural networks are employed to approximate unknown functions. The adaptation laws and the controllers are designed by employing the backstepping technique. The closed-loop system can be proven to be stable by using Lyapunov theorem. A simulation example is studied to validate the effectiveness of the scheme. PMID:25898325
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2013-01-01
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
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.
Adaptive model-based control systems and methods for controlling a gas turbine
NASA Technical Reports Server (NTRS)
Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)
2004-01-01
Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).
NASA Technical Reports Server (NTRS)
VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.
2014-01-01
Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a
Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.
Walking Flexibility after Hemispherectomy: Split-Belt Treadmill Adaptation and Feedback Control
ERIC Educational Resources Information Center
Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.
2009-01-01
Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…
NASA Technical Reports Server (NTRS)
Swift, David C.
1992-01-01
This project dealt with the application of a Direct Model Reference Adaptive Control algorithm to the control of a PUMA 560 Robotic Manipulator. This chapter will present some motivation for using Direct Model Reference Adaptive Control, followed by a brief historical review, the project goals, and a summary of the subsequent chapters.
ERIC Educational Resources Information Center
Obradovic, Jelena
2010-01-01
Homeless children show significant developmental delays across major domains of adaptation, yet research on protective processes that may contribute to resilient adaptation in this highly disadvantaged group of children is extremely rare. This study examined the role of effortful control for adaption in 58 homeless children, ages 5-6, during their…
PFC design via FRIT Approach for Adaptive Output Feedback Control of Discrete-time Systems
NASA Astrophysics Data System (ADS)
Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.
This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.
Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang
2015-01-01
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450
Electrowetting-Controlled Dual Liquid Prism for Adaptive Beam Steering
NASA Astrophysics Data System (ADS)
Cheng, Jiangtao
2015-03-01
The use of concentrating photovoltaic (CPV) technology has been the most promising method of harvesting solar radiation. These CPV systems often require motor-driven tracking devices to steer the sun's beams onto solar cells. The cost of maintaining these tracking systems is the primary inhibitor for widespread application. We aim to overcome the need for mechanical trackers through the use of an electrowetting-driven solar tracking (EWST) system. The electrowetting-driven solar tracking system consists of an array of novel electrowetting-controlled dual liquid prisms, which are filled with immiscible fluids that have large differences in refractive indices. The naturally formed meniscus between the fluids can function as a dynamic optical prism. Via the full-range modulation of the liquid prisms, incident sunlight can be adaptively tracked, steered, and focused onto CPV cells through a fixed optical condenser. Furthermore, unlike the conventional and cumbersome motor-driven tracking systems used today, the liquid prism system would be suitable for rooftop applications. The results of this project reveal that the EWST system has the potential to generate ~ 70% more green energy at 50% of the conventional capital cost.
Analysis of modified SMI method for adaptive array weight control
NASA Technical Reports Server (NTRS)
Dilsavor, R. L.; Moses, R. L.
1989-01-01
An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.
Control of the Adaptive Immune Response by Tumor Vasculature
Mauge, Laetitia; Terme, Magali; Tartour, Eric; Helley, Dominique
2014-01-01
The endothelium is nowadays described as an entire organ that regulates various processes: vascular tone, coagulation, inflammation, and immune cell trafficking, depending on the vascular site and its specific microenvironment as well as on endothelial cell-intrinsic mechanisms like epigenetic changes. In this review, we will focus on the control of the adaptive immune response by the tumor vasculature. In physiological conditions, the endothelium acts as a barrier regulating cell trafficking by specific expression of adhesion molecules enabling adhesion of immune cells on the vessel, and subsequent extravasation. This process is also dependent on chemokine and integrin expression, and on the type of junctions defining the permeability of the endothelium. Endothelial cells can also regulate immune cell activation. In fact, the endothelial layer can constitute immunological synapses due to its close interactions with immune cells, and the delivery of co-stimulatory or co-inhibitory signals. In tumor conditions, the vasculature is characterized by an abnormal vessel structure and permeability, and by a specific phenotype of endothelial cells. All these abnormalities lead to a modulation of intra-tumoral immune responses and contribute to the development of intra-tumoral immunosuppression, which is a major mechanism for promoting the development, progression, and treatment resistance of tumors. The in-depth analysis of these various abnormalities will help defining novel targets for the development of anti-tumoral treatments. Furthermore, eventual changes of the endothelial cell phenotype identified by plasma biomarkers could secondarily be selected to monitor treatment efficacy. PMID:24734218
Adaptive, Distributed Control of Constrained Multi-Agent Systems
NASA Technical Reports Server (NTRS)
Bieniawski, Stefan; Wolpert, David H.
2004-01-01
Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.
Adaptive Controller for Compact Fourier Transform Spectrometer with Space Applications
NASA Astrophysics Data System (ADS)
Keymeulen, D.; Yiu, P.; Berisford, D. F.; Hand, K. P.; Carlson, R. W.; Conroy, M.
2014-12-01
Here we present noise mitigation techniques developed as part of an adaptive controller for a very compact Compositional InfraRed Interferometric Spectrometer (CIRIS) implemented on a stand-alone field programmable gate array (FPGA) architecture with emphasis on space applications in high radiation environments such as Europa. CIRIS is a novel take on traditional Fourier Transform Spectrometers (FTS) and replaces linearly moving mirrors (characteristic of Michelson interferometers) with a constant-velocity rotating refractor to variably phase shift and alter the path length of incoming light. The design eschews a monochromatic reference laser typically used for sampling clock generation and instead utilizes constant time-sampling via internally generated clocks. This allows for a compact and robust device, making it ideal for spaceborne measurements in the near-IR to thermal-IR band (2-12 µm) on planetary exploration missions. The instrument's embedded microcontroller is implemented on a VIRTEX-5 FPGA and a PowerPC with the aim of sampling the instrument's detector and optical rotary encoder in order to construct interferograms. Subsequent onboard signal processing provides spectral immunity from the noise effects introduced by the compact design's removal of a reference laser and by the radiation encountered during space flight to destinations such as Europa. A variety of signal processing techniques including resampling, radiation peak removal, Fast Fourier Transform (FFT), spectral feature alignment, dispersion correction and calibration processes are applied to compose the sample spectrum in real-time with signal-to-noise-ratio (SNR) performance comparable to laser-based FTS designs in radiation-free environments. The instrument's FPGA controller is demonstrated with the FTS to characterize its noise mitigation techniques and highlight its suitability for implementation in space systems.
Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.; Pratt, S. G.
1979-01-01
The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.
Adaptive structures for precision controlled large space systems
NASA Technical Reports Server (NTRS)
Garba, John A.; Wada, Ben K.; Fanson, James L.
1991-01-01
The stringent accuracy and ground test validation requirements of some of the future space missions will require new approaches in structural design. Adaptive structures, structural systems that can vary their geometric congiguration as well as their physical properties, are primary candidates for meeting the functional requirements for such missions. Research performed in the development of such adaptive structural systems is described.
NASA Technical Reports Server (NTRS)
Wen, John T.; Kreutz, Kenneth; Bayard, David S.
1988-01-01
A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.
The stochastic control of the F-8C aircraft using the Multiple Model Adaptive Control (MMAC) method
NASA Technical Reports Server (NTRS)
Athans, M.; Dunn, K. P.; Greene, E. S.; Lee, W. H.; Sandel, N. R., Jr.
1975-01-01
The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called Multiple Model Adaptive Control method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the 'identification' aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.
Induction machine Direct Torque Control system based on fuzzy adaptive control
NASA Astrophysics Data System (ADS)
Li, Shi-ping; Yu, Yan; Jiao, Zhen-gang; Gu, Shu-sheng
2009-07-01
Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.
Selgrade, Brian P.
2014-01-01
During movement, errors are typically corrected only if they hinder performance. Preferential correction of task-relevant deviations is described by the minimal intervention principle but has not been demonstrated in the joints during locomotor adaptation. We studied hopping as a tractable model of locomotor adaptation of the joints within the context of a limb-force-specific task space. Subjects hopped while adapting to shifted visual feedback that induced them to increase peak ground reaction force (GRF). We hypothesized subjects would preferentially reduce task-relevant joint torque deviations over task-irrelevant deviations to increase peak GRF. We employed a modified uncontrolled manifold analysis to quantify task-relevant and task-irrelevant joint torque deviations for each individual hop cycle. As would be expected by the explicit goal of the task, peak GRF errors decreased in early adaptation before reaching steady state during late adaptation. Interestingly, during the early adaptation performance improvement phase, subjects reduced GRF errors by decreasing only the task-relevant joint torque deviations. In contrast, during the late adaption performance maintenance phase, all torque deviations decreased in unison regardless of task relevance. In deadaptation, when the shift in visual feedback was removed, all torque deviations decreased in unison, possibly because performance improvement was too rapid to detect changes in only the task-relevant dimension. We conclude that limb force adaptation in hopping switches from a minimal intervention strategy during performance improvement to a noise reduction strategy during performance maintenance, which may represent a general control strategy for locomotor adaptation of limb force in other bouncing gaits, such as running. PMID:25475343
Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin
2013-01-01
Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775
Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin
2013-01-01
Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
NASA Technical Reports Server (NTRS)
Patre, Parag; Joshi, Suresh M.
2011-01-01
Decentralized adaptive control is considered for systems consisting of multiple interconnected subsystems. It is assumed that each subsystem s parameters are uncertain and the interconnection parameters are not known. In addition, mismatch can exist between each subsystem and its reference model. A strictly decentralized adaptive control scheme is developed, wherein each subsystem has access only to its own state but has the knowledge of all reference model states. The mismatch is estimated online for each subsystem and the mismatch estimates are used to adaptively modify the corresponding reference models. The adaptive control scheme is extended to the case with actuator failures in addition to mismatch.
Adaptive tuning of feedback gain in time-delayed feedback control
NASA Astrophysics Data System (ADS)
Lehnert, J.; Hövel, P.; Flunkert, V.; Guzenko, P. Yu.; Fradkov, A. L.; Schöll, E.
2011-12-01
We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions.
Adaptive tuning of feedback gain in time-delayed feedback control.
Lehnert, J; Hövel, P; Flunkert, V; Guzenko, P Yu; Fradkov, A L; Schöll, E
2011-12-01
We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions. PMID:22225348
Control of innate and adaptive immunity by the inflammasome
Ciraci, Ceren; Janczy, John R.; Sutterwala, Fayyaz S.; Cassel, Suzanne L.
2012-01-01
The importance of innate immunity lies not only in directly confronting pathogenic and non-pathogenic insults but also in instructing the development of an efficient adaptive immune response. The Nlrp3 inflammasome provides a platform for the activation of caspase-1 with the subsequent processing and secretion of IL-1 family members. Given the importance of IL-1 in a variety of inflammatory diseases, understanding the role of Nlrp3 inflammasome in the initiation of innate and adaptive immune responses cannot be overstated. This review examines recent advances in inflammasome biology with an emphasis on its roles in sterile inflammation and triggering of adaptive immune responses. PMID:22841804
Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems
NASA Technical Reports Server (NTRS)
Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)
2014-01-01
Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.
Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.
2010-01-01
This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.
NASA Technical Reports Server (NTRS)
Hanson, Curt
2014-01-01
An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority.
NASA Technical Reports Server (NTRS)
Boussalis, Dhemetrios; Wang, Shyh J.
1992-01-01
This paper presents a method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems.
Mood states influence cognitive control: the case of conflict adaptation.
Schuch, Stefanie; Koch, Iring
2015-09-01
Conflict adaptation can be measured by the "congruency sequence effect", denoting the reduction of congruency effects after incongruent trials (where response conflict occurs) relative to congruent trials (without response conflict). Recently, it has been reported that conflict adaptation is larger in negative mood than in positive mood (van Steenbergen et al., Psychological Science 21:1629-1634, 2010). We conducted two experiments further investigating this important finding. Two different interference paradigms were applied to measure conflict adaptation: Experiment 1 was a Flanker task, Experiment 2 was a Stroop-like task. To get as pure a measure of conflict adaptation as possible, we minimized the influence of trial-to-trial priming effects by excluding all kinds of stimulus repetitions. Mood states were induced by presenting film clips with emotional content prior to the interference task. Three mood states were manipulated between subjects: amused, anxious, and sad. Across both interference paradigms, we consistently found conflict adaptation in negative, but not in positive mood. Taken together with van Steenbergen et al. (Psychological Science 21:1629-1634, 2010) findings, the results suggest that the negative-mood-triggered increase in conflict adaptation is a general phenomenon that occurs independently of the particular mood-induction procedure and interference paradigm involved. PMID:25100233
NASA Astrophysics Data System (ADS)
Xie, Haibo; Liu, Zhibin; Yang, Huayong
2016-05-01
Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.
NASA Astrophysics Data System (ADS)
Xie, Haibo; Liu, Zhibin; Yang, Huayong
2016-04-01
Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.
Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.
Heydari, Ali; Balakrishnan, Sivasubramanya N
2013-01-01
To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline. PMID:24808214
Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.
2010-01-01
This paper focuses on the analysis and tuning of a controller based on the Adaptive Control Technology for Safe Flight (ACTS) architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller s ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft s state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.
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.
NASA Technical Reports Server (NTRS)
Balas, Mark; Frost, Susan
2012-01-01
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.
The beauty of simple adaptive control and new developments in nonlinear systems stability analysis
Barkana, Itzhak
2014-12-10
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.
The beauty of simple adaptive control and new developments in nonlinear systems stability analysis
NASA Astrophysics Data System (ADS)
Barkana, Itzhak
2014-12-01
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.
REVIEW: Internal models in sensorimotor integration: perspectives from adaptive control theory
NASA Astrophysics Data System (ADS)
Tin, Chung; Poon, Chi-Sang
2005-09-01
Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems—such as sensorimotor prediction or the resolution of vestibular sensory ambiguity—is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.
NASA Astrophysics Data System (ADS)
Phu, Do Xuan; Shah, Kruti; Choi, Seung-Bok
2014-06-01
This paper presents a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological (MR) fluid damper in order to validate the effectiveness of the control performance. An interval type 2 fuzzy model is built, and then combined with modified adaptive control to achieve the desired damping force. In the formulation of the new adaptive controller, an enhanced iterative algorithm is integrated with the fuzzy model to decrease the time of calculation (D Wu 2013 IEEE Trans. Fuzzy Syst. 21 80-99) and the control algorithm is synthesized based on the {{H}^{\\infty }} tracking technique. In addition, for the verification of good control performance of the proposed controller, a cylindrical MR damper which can be applied to the vibration control of a washing machine is designed and manufactured. For the operating fluid, a recently developed plate-like particle-based MR fluid is used instead of a conventional MR fluid featuring spherical particles. To highlight the control performance of the proposed controller, two existing adaptive fuzzy control algorithms proposed by other researchers are adopted and altered for a comparative study. It is demonstrated from both simulation and experiment that the proposed new adaptive controller shows better performance of damping force control in terms of response time and tracking accuracy than the existing approaches.
Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.
Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min
2014-01-01
An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results. PMID:25147871
NASA Astrophysics Data System (ADS)
Mokaddem, S.; Khaber, F.
2008-06-01
This work presents a development of adaptive type-1 and type-2 fuzzy controls for uncertain nonlinear systems. Using the adaptive type-1 fuzzy control, the dynamic of the nonlinear systems is approximated with type-1 fuzzy systems whose parameters are adjusted by appropriate law adaptation. For adaptive type-2 fuzzy control, the dynamic of the nonlinear systems is approximated with interval type-2 fuzzy systems. The use of this type-2 control requires an additional operation witch is the type reduction, in comparing with typ-1 control. The closed-loop system stability is guaranteed by the Lyaponov synthesis. To show the performance of the developed controls, a comparative study is realized through the application of these controls so that an inverted pendulum tracks a given trajectory in presence of disturbances.
An adaptive neuro-control system of synchronous generator for power system stabilization
Kobayashi, Takenori; Yokoyama, Akihiko
1996-09-01
This paper proposes a nonlinear adaptive generator control system using neural networks, called an adaptive neuro-control system (ANCS). This system generates supplementary control signals to conventional controllers and works adaptively in response to changes in operating conditions and network configuration. Through digital time simulations for a one-machine infinite bus test power system, the control performance of the ANCS and advanced controllers such as a linear optimal regulator and a self-tuning regulator is evaluated from the viewpoint of stability enhancement. As a result, the proposed ANCS using neural networks with nonlinear characteristics improves system damping more effectively and more adaptively than the other two controllers designed for the linearized model of the power system.
Deng, Hua; Li, Han-Xiong; Wu, Yi-Hu
2008-09-01
A new feedback-linearization-based neural network (NN) adaptive control is proposed for unknown nonaffine nonlinear discrete-time systems. An equivalent model in affine-like form is first derived for the original nonaffine discrete-time systems as feedback linearization methods cannot be implemented for such systems. Then, feedback linearization adaptive control is implemented based on the affine-like equivalent model identified with neural networks. Pretraining is not required and the weights of the neural networks used in adaptive control are directly updated online based on the input-output measurement. The dead-zone technique is used to remove the requirement of persistence excitation during the adaptation. With the proposed neural network adaptive control, stability and performance of the closed-loop system are rigorously established. Illustrated examples are provided to validate the theoretical findings. PMID:18779092
CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots.
Liu, Chengju; Chen, Qijun; Wang, Danwei
2011-06-01
This paper deals with the locomotion control of quadruped robots inspired by the biological concept of central pattern generator (CPG). A control architecture is proposed with a 3-D workspace trajectory generator and a motion engine. The workspace trajectory generator generates adaptive workspace trajectories based on CPGs, and the motion engine realizes joint motion imputes. The proposed architecture is able to generate adaptive workspace trajectories online by tuning the parameters of the CPG network to adapt to various terrains. With feedback information, a quadruped robot can walk through various terrains with adaptive joint control signals. A quadruped platform AIBO is used to validate the proposed locomotion control system. The experimental results confirm the effectiveness of the proposed control architecture. A comparison by experiments shows the superiority of the proposed method against the traditional CPG-joint-space control method. PMID:21216715
Adaptive Control of a Serial-in-Parallel Robotic Rehabilitation Device
Pehlivan, Ali Utku; Sergi, Fabrizio; O’Malley, Marcia K.
2013-01-01
Robotic rehabilitation is an effective platform for sensorimotor training after neurological injuries. In this paper, an adaptive controller is developed and implemented for the RiceWrist, a serial-in-parallel robot mechanism for upper extremity robotic rehabilitation. The model-based adaptive controller implementation requires a closed form dynamic model, valid for a restricted domain of generalized coordinates. We have used an existing method to define this domain and verify that the domain is widely within the range of admissible tasks required for the considered application (movements-based wrist and forearm rehabilitation). Simulation and experimental results that compare the performance of the adaptive controller to a proportional- derivative controller show that the trajectory tracking performance of the adaptive controller is better compared to the performance of a PD controller using the same values of feed-back gains. Further, comparable absolute error performance is obtained with the adaptive controller for feedback gains nearly one third that required for the PD controller. With the lower gains used in the adaptive controller, good tracking performance is achieved with a more compliant controller that will allow the subject to indicate their ability to independently initiate and maintain movement during a rehabilitation session. PMID:24187231
Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Balas, Mark J.; Wright, Alan D.
2009-01-01
Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. 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. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.