Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

PubMed

Moore, J H

1995-06-01

A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

Assisted closed-loop optimization of SSVEP-BCI efficiency

PubMed Central

Fernandez-Vargas, Jacobo; Pfaff, Hanns U.; Rodríguez, Francisco B.; Varona, Pablo

2012-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research. PMID:23443214

Assisted closed-loop optimization of SSVEP-BCI efficiency.

PubMed

Fernandez-Vargas, Jacobo; Pfaff, Hanns U; Rodríguez, Francisco B; Varona, Pablo

2013-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.

An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia

NASA Astrophysics Data System (ADS)

Yang, Yuxiao; Shanechi, Maryam M.

2016-12-01

Objective. Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. Approach. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. Main results. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. Significance. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost-saving and therapeutic benefits.

An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia.

PubMed

Yang, Yuxiao; Shanechi, Maryam M

2016-12-01

Design of closed-loop anesthetic delivery (CLAD) systems is an important topic, particularly for medically induced coma, which needs to be maintained for long periods. Current CLADs for medically induced coma require a separate offline experiment for model parameter estimation, which causes interruption in treatment and is difficult to perform. Also, CLADs may exhibit bias due to inherent time-variation and non-stationarity, and may have large infusion rate variations at steady state. Finally, current CLADs lack theoretical performance guarantees. We develop the first adaptive CLAD for medically induced coma, which addresses these limitations. Further, we extend our adaptive system to be generalizable to other states of anesthesia. We designed general parametric pharmacodynamic, pharmacokinetic and neural observation models with associated guidelines, and derived a novel adaptive controller. We further penalized large steady-state drug infusion rate variations in the controller. We derived theoretical guarantees that the adaptive system has zero steady-state bias. Using simulations that resembled real time-varying and noisy environments, we tested the closed-loop system for control of two different anesthetic states, burst suppression in medically induced coma and unconsciousness in general anesthesia. In 1200 simulations, the adaptive system achieved precise control of both anesthetic states despite non-stationarity, time-variation, noise, and no initial parameter knowledge. In both cases, the adaptive system performed close to a baseline system that knew the parameters exactly. In contrast, a non-adaptive system resulted in large steady-state bias and error. The adaptive system also resulted in significantly smaller steady-state infusion rate variations compared to prior systems. These results have significant implications for clinically viable CLAD design for a wide range of anesthetic states, with potential cost-saving and therapeutic benefits.

Analytical solutions to optimal underactuated spacecraft formation reconfiguration

NASA Astrophysics Data System (ADS)

Huang, Xu; Yan, Ye; Zhou, Yang

2015-11-01

Underactuated systems can generally be defined as systems with fewer number of control inputs than that of the degrees of freedom to be controlled. In this paper, analytical solutions to optimal underactuated spacecraft formation reconfiguration without either the radial or the in-track control are derived. By using a linear dynamical model of underactuated spacecraft formation in circular orbits, controllability analysis is conducted for either underactuated case. Indirect optimization methods based on the minimum principle are then introduced to generate analytical solutions to optimal open-loop underactuated reconfiguration problems. Both fixed and free final conditions constraints are considered for either underactuated case and comparisons between these two final conditions indicate that the optimal control strategies with free final conditions require less control efforts than those with the fixed ones. Meanwhile, closed-loop adaptive sliding mode controllers for both underactuated cases are designed to guarantee optimal trajectory tracking in the presence of unmatched external perturbations, linearization errors, and system uncertainties. The adaptation laws are designed via a Lyapunov-based method to ensure the overall stability of the closed-loop system. The explicit expressions of the terminal convergent regions of each system states have also been obtained. Numerical simulations demonstrate the validity and feasibility of the proposed open-loop and closed-loop control schemes for optimal underactuated spacecraft formation reconfiguration in circular orbits.

Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems.

PubMed

Wang, Cong; Wang, Min; Liu, Tengfei; Hill, David J

2012-10-01

This paper studies learning from adaptive neural control (ANC) for a class of nonlinear strict-feedback systems with unknown affine terms. To achieve the purpose of learning, a simple input-to-state stability (ISS) modular ANC method is first presented to ensure the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in finite time. Subsequently, it is proven that learning with the proposed stable ISS-modular ANC can be achieved. The cascade structure and unknown affine terms of the considered systems make it very difficult to achieve learning using existing methods. To overcome these difficulties, the stable closed-loop system in the control process is decomposed into a series of linear time-varying (LTV) perturbed subsystems with the appropriate state transformation. Using a recursive design, the partial persistent excitation condition for the radial basis function neural network (NN) is established, which guarantees exponential stability of LTV perturbed subsystems. Consequently, accurate approximation of the closed-loop system dynamics is achieved in a local region along recurrent orbits of closed-loop signals, and learning is implemented during a closed-loop feedback control process. The learned knowledge is reused to achieve stability and an improved performance, thereby avoiding the tremendous repeated training process of NNs. Simulation studies are given to demonstrate the effectiveness of the proposed method.

Demonstration of a vectorial optical field generator with adaptive close loop control.

PubMed

Chen, Jian; Kong, Lingjiang; Zhan, Qiwen

2017-12-01

We experimentally demonstrate a vectorial optical field generator (VOF-Gen) with an adaptive close loop control. The close loop control capability is illustrated with the calibration of polarization modulation of the system. To calibrate the polarization ratio modulation, we generate 45° linearly polarized beam and make it propagate through a linear analyzer whose transmission axis is orthogonal to the incident beam. For the retardation calibration, circularly polarized beam is employed and a circular polarization analyzer with the opposite chirality is placed in front of the CCD as the detector. In both cases, the close loop control automatically changes the value of the corresponding calibration parameters in the pre-set ranges to generate the phase patterns applied to the spatial light modulators and records the intensity distribution of the output beam by the CCD camera. The optimized calibration parameters are determined corresponding to the minimum total intensity in each case. Several typical kinds of vectorial optical beams are created with and without the obtained calibration parameters, and the full Stokes parameter measurements are carried out to quantitatively analyze the polarization distribution of the generated beams. The comparisons among these results clearly show that the obtained calibration parameters could remarkably improve the accuracy of the polarization modulation of the VOF-Gen, especially for generating elliptically polarized beam with large ellipticity, indicating the significance of the presented close loop in enhancing the performance of the VOF-Gen.

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

PubMed

Wang, Min; Wang, Cong

2015-06-01

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

Fuzzy control for closed-loop, patient-specific hypnosis in intraoperative patients: a simulation study.

PubMed

Moore, Brett L; Pyeatt, Larry D; Doufas, Anthony G

2009-01-01

Research has demonstrated the efficacy of closed-loop control of anesthesia using bispectral index (BIS) as the controlled variable, and the recent development of model-based, patient-adaptive systems has considerably improved anesthetic control. To further explore the use of model-based control in anesthesia, we investigated the application of fuzzy control in the delivery of patient-specific propofol-induced hypnosis. In simulated intraoperative patients, the fuzzy controller demonstrated clinically acceptable performance, suggesting that further study is warranted.

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

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

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Keller, Dennis J.

2001-01-01

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

Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification

NASA Astrophysics Data System (ADS)

Sobolic, Frantisek M.

Retrospective cost adaptive control (RCAC) is a discrete-time direct adaptive control algorithm for stabilization, command following, and disturbance rejection. RCAC is known to work on systems given minimal modeling information which is the leading numerator coefficient and any nonminimum-phase (NMP) zeros of the plant transfer function. This information is normally needed a priori and is key in the development of the filter, also known as the target model, within the retrospective performance variable. A novel approach to alleviate the need for prior modeling of both the leading coefficient of the plant transfer function as well as any NMP zeros is developed. The extension to the RCAC algorithm is the use of concurrent optimization of both the target model and the controller coefficients. Concurrent optimization of the target model and controller coefficients is a quadratic optimization problem in the target model and controller coefficients separately. However, this optimization problem is not convex as a joint function of both variables, and therefore nonconvex optimization methods are needed. Finally, insights within RCAC that include intercalated injection between the controller numerator and the denominator, unveil the workings of RCAC fitting a specific closed-loop transfer function to the target model. We exploit this interpretation by investigating several closed-loop identification architectures in order to extract this information for use in the target model.

A review of active control approaches in stabilizing combustion systems in aerospace industry

NASA Astrophysics Data System (ADS)

Zhao, Dan; Lu, Zhengli; Zhao, He; Li, X. Y.; Wang, Bing; Liu, Peijin

2018-02-01

Self-sustained combustion instabilities are one of the most plaguing challenges and problems in lean-conditioned propulsion and land-based engine systems, such as rocket motors, gas turbines, industrial furnace and boilers, and turbo-jet thrust augmenters. Either passive or active control in open- or closed-loop configurations can be implemented to mitigate such instabilities. One of the classical disadvantages of passive control is that it is only implementable to a designed combustor over a limited frequency range and can not respond to the changes in operating conditions. Compared with passive control approaches, active control, especially in closed-loop configuration is more adaptive and has inherent capacity to be implemented in practice. The key components in closed-loop active control are 1) sensor, 2) controller (optimization algorithm) and 3) dynamic actuator. The present work is to outline the current status, technical challenges and development progress of the active control approaches (in open- or closed-loop configurations). A brief description of feedback control, adaptive control, model-based control and sliding mode control are provided first by introducing a simplified Rijke-type combustion system. The modelled combustion system provides an invaluable platform to evaluate the performance of these feedback controllers and a transient growth controller. The performance of these controllers are compared and discussed. An outline of theoretical, numerical and experimental investigations are then provided to overview the research and development progress made during the last 4 decades. Finally, potential, challenges and issues involved with the design, application and implementation of active combustion control strategies on a practical engine system are highlighted.

On-off closed-loop control of vagus nerve stimulation for the adaptation of heart rate.

PubMed

Ugalde, Hector Romero; Le Rolle, Virginie; Bel, Alain; Bonnet, Jean-Luc; Andreu, David; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo I

2014-01-01

Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop approaches may be necessary to optimize the therapy and minimize side effects of neuro-stimulation devices. In this paper, we describe a prototype system for real-time control of the instantaneous heart rate, working synchronously with the heart period. As a first step, an on-off control method has been integrated. The system is evaluated on one sheep with induced heart failure, showing the interest of the proposed approach.

Computer simulation of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Vogt, William G.; Mickle, Marlin H.; Zipf, Mark E.; Kucuk, Senol

1989-01-01

The objective was to develop a computerized adaptive pilot model for the computer model of the research aircraft, the Harrier II AV-8B V/STOL with special emphasis on propulsion control. In fact, two versions of the adaptive pilot are given. The first, simply called the Adaptive Control Model (ACM) of a pilot includes a parameter estimation algorithm for the parameters of the aircraft and an adaption scheme based on the root locus of the poles of the pilot controlled aircraft. The second, called the Optimal Control Model of the pilot (OCM), includes an adaption algorithm and an optimal control algorithm. These computer simulations were developed as a part of the ongoing research program in pilot model simulation supported by NASA Lewis from April 1, 1985 to August 30, 1986 under NASA Grant NAG 3-606 and from September 1, 1986 through November 30, 1988 under NASA Grant NAG 3-729. Once installed, these pilot models permitted the computer simulation of the pilot model to close all of the control loops normally closed by a pilot actually manipulating the control variables. The current version of this has permitted a baseline comparison of various qualitative and quantitative performance indices for propulsion control, the control loops and the work load on the pilot. Actual data for an aircraft flown by a human pilot furnished by NASA was compared to the outputs furnished by the computerized pilot and found to be favorable.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

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 generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

Automated hybrid closed-loop control with a proportional-integral-derivative based system in adolescents and adults with type 1 diabetes: individualizing settings for optimal performance.

PubMed

Ly, Trang T; Weinzimer, Stuart A; Maahs, David M; Sherr, Jennifer L; Roy, Anirban; Grosman, Benyamin; Cantwell, Martin; Kurtz, Natalie; Carria, Lori; Messer, Laurel; von Eyben, Rie; Buckingham, Bruce A

2017-08-01

Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70-180 mg/dL (3.9-10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes. We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4-5 days. The overall mean percentage of time in range (70-180 mg/dL, 3.9-10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort. Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Real-time closed-loop control of cognitive load in neurological patients during robot-assisted gait training.

PubMed

Koenig, Alexander; Novak, Domen; Omlin, Ximena; Pulfer, Michael; Perreault, Eric; Zimmerli, Lukas; Mihelj, Matjaz; Riener, Robert

2011-08-01

Cognitively challenging training sessions during robot-assisted gait training after stroke were shown to be key requirements for the success of rehabilitation. Despite a broad variability of cognitive impairments amongst the stroke population, current rehabilitation environments do not adapt to the cognitive capabilities of the patient, as cognitive load cannot be objectively assessed in real-time. We provided healthy subjects and stroke patients with a virtual task during robot-assisted gait training, which allowed modulating cognitive load by adapting the difficulty level of the task. We quantified the cognitive load of stroke patients by using psychophysiological measurements and performance data. In open-loop experiments with healthy subjects and stroke patients, we obtained training data for a linear, adaptive classifier that estimated the current cognitive load of patients in real-time. We verified our classification results via questionnaires and obtained 88% correct classification in healthy subjects and 75% in patients. Using the pre-trained, adaptive classifier, we closed the cognitive control loop around healthy subjects and stroke patients by automatically adapting the difficulty level of the virtual task in real-time such that patients were neither cognitively overloaded nor under-challenged. © 2011 IEEE

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 the EEG index is high) results in a marked decrease of the vigilance decrement over a 40 minute session. This effect is in direct contrast to performance of a positive feedback group, as well as a number of other control groups which demonstrated the typical vigilance decrement. Interestingly, however, the negative feedback group performed at virtually the same level as a yoked control group. The yoked control group received the same order of changes in event rate that were generated by the negative feedback subjects using the closed-loop system. Thus it would appear to be possible to optimize vigilance performance by controlling the stimuli which subjects are asked to process.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

PubMed

Ewing, Kate C; Fairclough, Stephen H; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop

PubMed Central

Ewing, Kate C.; Fairclough, Stephen H.; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed. PMID:27242486

Smart Braid Feedback for the Closed-Loop Control of Soft Robotic Systems.

PubMed

Felt, Wyatt; Chin, Khai Yi; Remy, C David

2017-09-01

This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. As truly soft sensor solutions are still in their infancy, motion control of soft robots has so far relied on laboratory-based sensing systems such as motion capture, electromagnetic (EM) tracking, or Fiber Bragg Gratings. In this article, we used embedded flexible sensors known as Smart Braids to sense the contraction of McKibben muscles through changes in inductance. We evaluated closed-loop control on two systems: a revolute joint and a planar, one degree of freedom continuum manipulator. In the revolute joint, our proposed controller compensated for elasticity in the actuator connections. The Smart Braid feedback allowed motion control with a steady-state root-mean-square (RMS) error of [1.5]°. In the continuum manipulator, Smart Braid feedback enabled tracking of the desired tip angle with a steady-state RMS error of [1.25]°. This work demonstrates that Smart Braid sensors can provide accurate position feedback in closed-loop motion control suitable for field applications of soft robotic systems.

Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

PubMed

Bagheri, Pedram; Sun, Qiao

2016-07-01

In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer

PubMed Central

Miao, Zhidong; Liu, Dake

2017-01-01

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power. PMID:28763011

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer.

PubMed

Miao, Zhidong; Liu, Dake; Gong, Chen

2017-08-01

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power.

Ground-based adaptive optics coronagraphic performance under closed-loop predictive control

NASA Astrophysics Data System (ADS)

Males, Jared R.; Guyon, Olivier

2018-01-01

The discovery of the exoplanet Proxima b highlights the potential for the coming generation of giant segmented mirror telescopes (GSMTs) to characterize terrestrial-potentially habitable-planets orbiting nearby stars with direct imaging. This will require continued development and implementation of optimized adaptive optics systems feeding coronagraphs on the GSMTs. Such development should proceed with an understanding of the fundamental limits imposed by atmospheric turbulence. Here, we seek to address this question with a semianalytic framework for calculating the postcoronagraph contrast in a closed-loop adaptive optics system. We do this starting with the temporal power spectra of the Fourier basis calculated assuming frozen flow turbulence, and then apply closed-loop transfer functions. We include the benefits of a simple predictive controller, which we show could provide over a factor of 1400 gain in raw point spread function contrast at 1 λ/D on bright stars, and more than a factor of 30 gain on an I=7.5 mag star such as Proxima. More sophisticated predictive control can be expected to improve this even further. Assuming a photon-noise limited observing technique such as high-dispersion coronagraphy, these gains in raw contrast will decrease integration times by the same large factors. Predictive control of atmospheric turbulence should therefore be seen as one of the key technologies that will enable ground-based telescopes to characterize terrestrial planets.

First on-sky demonstration of the piezoelectric adaptive secondary mirror.

PubMed

Guo, Youming; Zhang, Ang; Fan, Xinlong; Rao, Changhui; Wei, Ling; Xian, Hao; Wei, Kai; Zhang, Xiaojun; Guan, Chunlin; Li, Min; Zhou, Luchun; Jin, Kai; Zhang, Junbo; Deng, Jijiang; Zhou, Longfeng; Chen, Hao; Zhang, Xuejun; Zhang, Yudong

2016-12-15

We propose using a piezoelectric adaptive secondary mirror (PASM) in the medium-sized adaptive telescopes with a 2-4 m aperture for structure and control simplification by utilizing the piezoelectric actuators in contrast with the voice-coil adaptive secondary mirror. A closed-loop experimental setup was built for on-sky demonstration of the 73-element PASM developed by our laboratory. In this Letter, the PASM and the closed-loop adaptive optics system are introduced. High-resolution stellar images were obtained by using the PASM to correct high-order wavefront errors in May 2016. To the best of our knowledge, this is the first successful on-sky demonstration of the PASM. The results show that with the PASM as the deformable mirror, the angular resolution of the 1.8 m telescope can be effectively improved.

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.

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.

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

1992-01-01

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

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.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Closed-Loop Optimal Control Implementations for Space Applications

DTIC Science & Technology

2016-12-01

analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to feedback on the...through the analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering

Nonlinear predictive control for adaptive adjustments of deep brain stimulation parameters in basal ganglia-thalamic network.

PubMed

Su, Fei; Wang, Jiang; Niu, Shuangxia; Li, Huiyan; Deng, Bin; Liu, Chen; Wei, Xile

2018-02-01

The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters. Closed-loop stimulation is one method to realize the frequent adjustment of stimulation parameters. This paper introduced the nonlinear predictive control method into the online adjustment of DBS amplitude and frequency. This approach was tested in a computational model of basal ganglia-thalamic network. The autoregressive Volterra model was used to identify the process model based on physiological data. Simulation results illustrated the efficiency of closed-loop stimulation methods (amplitude adjustment and frequency adjustment) in improving the relay reliability of thalamic neurons compared with the PD state. Besides, compared with the 130Hz constant DBS the closed-loop stimulation methods can significantly reduce the energy consumption. Through the analysis of inter-spike-intervals (ISIs) distribution of basal ganglia neurons, the evoked network activity by the closed-loop frequency adjustment stimulation was closer to the normal state. Copyright © 2017 Elsevier Ltd. All rights reserved.

Safe Glycemic Management during Closed-Loop Treatment of Type 1 Diabetes: The Role of Glucagon, Use of Multiple Sensors, and Compensation for Stress Hyperglycemia

PubMed Central

Ward, W Kenneth; Castle, Jessica R; Youssef, Joseph El

2011-01-01

Patients with type 1 diabetes mellitus (T1DM) must make frequent decisions and lifestyle adjustments in order to manage their disorder. Automated treatment would reduce the need for these self-management decisions and reduce the risk for long-term complications. Investigators in the field of closed-loop glycemic control systems are now moving from inpatient to outpatient testing of such systems. As outpatient systems are developed, the element of safety increases in importance. One such concern is the risk for hypoglycemia, due in part to the delayed onset and prolonged action duration of currently available subcutaneous insulin preparations. We found that, as compared to an insulin-only closed-loop system, a system that also delivers glucagon when needed led to substantially less hypoglycemia. Though the capability of glucagon delivery would mandate the need for a second hormone chamber, glucagon in small doses is tolerated very well. People with T1DM often develop hyperglycemia from emotional stress or medical stress. Automated closed-loop systems should be able to detect such changes in insulin sensitivity and adapt insulin delivery accordingly. We recently verified the adaptability of a model-based closed-loop system in which the gain factors that govern a proportional-integral-derivative-like system are adjusted according to frequently measured insulin sensitivity. Automated systems can be tested by physical exercise to increase glucose uptake and insulin sensitivity or by administering corticosteroids to reduce insulin sensitivity. Another source of risk in closed-loop systems is suboptimal performance of amperometric glucose sensors. Inaccuracy can result from calibration error, biofouling, and current drift. We found that concurrent use of more than one sensor typically leads to better sensor accuracy than use of a single sensor. For example, using the average of two sensors substantially reduces the proportion of large sensor errors. The use of more than two allows the use of voting algorithms, which can temporarily exclude a sensor whose signal is outlying. Elements such as the use of glucagon to minimize hypoglycemia, adaptation to changes in insulin sensitivity, and sensor redundancy will likely increase safety during outpatient use of closed-loop glycemic control systems. PMID:22226254

Close-loop performance of a high precision deflectometry controlled deformable mirror (DCDM) unit for wavefront correction in adaptive optics system

NASA Astrophysics Data System (ADS)

Huang, Lei; Zhou, Chenlu; Zhao, Wenchuan; Choi, Heejoo; Graves, Logan; Kim, Daewook

2017-06-01

We present a high precision deflectometry system (DS) controlled deformable mirror (DM) solution for optical system. Different from wavefront and non-wavefront system, the DS and the DM are set to be an individual integrated DCDM unit and can be installed in one base plate. In the DCDM unit, the DS can directly provide the influence functions and surface shape of the DM to the industrial computer in any adaptive optics system. As an integrated adaptive unit, the DCDM unit could be put into various optical systems to realize aberration compensation. In this paper, the configuration and principle of the DCDM unit is introduced first. Theoretical simulation on the close-loop performance of the DCDM unit is carried out. Finally, a verification experiment is proposed to verify the compensation capability of the DCDM unit.

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

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

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

Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure.

PubMed

Sun, Yumei; Chen, Bing; Lin, Chong; Wang, Honghong

2017-09-18

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.

Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.

PubMed

Gao, Hui; Song, Yongduan; Wen, Changyun

In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.

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.

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

PubMed

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

2017-03-01

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

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

NASA Astrophysics Data System (ADS)

Liu, Chun; Jiang, Bin; Zhang, Ke

2018-03-01

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.

Implementation and on-sky results of an optimal wavefront controller for the MMT NGS adaptive optics system

NASA Astrophysics Data System (ADS)

Powell, Keith B.; Vaitheeswaran, Vidhya

2010-07-01

The MMT observatory has recently implemented and tested an optimal wavefront controller for the NGS adaptive optics system. Open loop atmospheric data collected at the telescope is used as the input to a MATLAB based analytical model. The model uses nonlinear constrained minimization to determine controller gains and optimize the system performance. The real-time controller performing the adaptive optics close loop operation is implemented on a dedicated high performance PC based quad core server. The controller algorithm is written in C and uses the GNU scientific library for linear algebra. Tests at the MMT confirmed the optimal controller significantly reduced the residual RMS wavefront compared with the previous controller. Significant reductions in image FWHM and increased peak intensities were obtained in J, H and K-bands. The optimal PID controller is now operating as the baseline wavefront controller for the MMT NGS-AO system.

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.

Laboratory demonstrations on a pyramid wavefront sensor without modulation for closed-loop adaptive optics system.

PubMed

Wang, Shengqian; Rao, Changhui; Xian, Hao; Zhang, Jianlin; Wang, Jianxin; Liu, Zheng

2011-04-25

The feasibility and performance of the pyramid wavefront sensor without modulation used in closed-loop adaptive optics system is investigated in this paper. The theory concepts and some simulation results are given to describe the detection trend and the linearity range of such a sensor with the aim to better understand its properties, and then a laboratory setup of the adaptive optics system based on this sensor and the liquid-crystal spatial light modulator is built. The correction results for the individual Zernike aberrations and the Kolmogorov phase screens are presented to demonstrate that the pyramid wavefront sensor without modulation can work as expected for closed-loop adaptive optics system.

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB.

PubMed

Mansouri, Misagh; Reinbolt, Jeffrey A

2012-05-11

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB's variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1s (OpenSim) to 2.9s (MATLAB). For the closed-loop case, a proportional-integral-derivative controller was used to successfully balance a pole on model's hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB

PubMed Central

Mansouri, Misagh; Reinbolt, Jeffrey A.

2013-01-01

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB’s variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1 s (OpenSim) to 2.9 s (MATLAB). For the closed-loop case, a proportional–integral–derivative controller was used to successfully balance a pole on model’s hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions. PMID:22464351

Wavefront control in adaptive microscopy using Shack-Hartmann sensors with arbitrarily shaped pupils.

PubMed

Dong, Bing; Booth, Martin J

2018-01-22

In adaptive optical microscopy of thick biological tissue, strong scattering and aberrations can change the effective pupil shape by rendering some Shack-Hartmann spots unusable. The change of pupil shape leads to a change of wavefront reconstruction or control matrix that should be updated accordingly. Modified slope and modal wavefront control methods based on measurements of a Shack-Hartmann wavefront sensor are proposed to accommodate an arbitrarily shaped pupil. Furthermore, we present partial wavefront control methods that remove specific aberration modes like tip, tilt and defocus from the control loop. The proposed control methods were investigated and compared by simulation using experimentally obtained aberration data. The performance was then tested experimentally through closed-loop aberration corrections using an obscured pupil.

Adaptive Nonlinear Tracking Control of Kinematically Redundant Robot Manipulators with Sub-Task Extensions

DTIC Science & Technology

2005-01-01

C. Hughes, Spacecraft Attitude Dynamics, New York, NY: Wiley, 1994. [8] H. K. Khalil, “Adaptive Output Feedback Control of Non- linear Systems...Closed-Loop Manipulator Control Using Quaternion Feedback ”, IEEE Trans. Robotics and Automation, Vol. 4, No. 4, pp. 434-440, (1988). [23] E...full-state feedback quaternion based controller de- veloped in [5] and focuses on the design of a general sub-task controller. This sub-task controller

An optimal open/closed-loop control method with application to a pre-stressed thin duralumin plate

NASA Astrophysics Data System (ADS)

Nadimpalli, Sruthi Raju

The excessive vibrations of a pre-stressed duralumin plate, suppressed by a combination of open-loop and closed-loop controls, also known as open/closed-loop control, is studied in this thesis. The two primary steps involved in this process are: Step (I) with an assumption that the closed-loop control law is proportional, obtain the optimal open-loop control by direct minimization of the performance measure consisting of energy at terminal time and a penalty on open-loop control force via calculus of variations. If the performance measure also involves a penalty on closed-loop control effort then a Fourier based method is utilized. Step (II) the energy at terminal time is minimized numerically to obtain optimal values of feedback gains. The optimal closed-loop control gains obtained are used to describe the displacement and the velocity of open-loop, closed-loop and open/closed-loop controlled duralumin plate.

Adaptive identification and control of structural dynamics systems using recursive lattice filters

NASA Technical Reports Server (NTRS)

Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

1985-01-01

A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

PubMed

Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

2013-12-01

Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

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.

Bio-Inspired Controller on an FPGA Applied to Closed-Loop Diaphragmatic Stimulation

PubMed Central

Zbrzeski, Adeline; Bornat, Yannick; Hillen, Brian; Siu, Ricardo; Abbas, James; Jung, Ranu; Renaud, Sylvie

2016-01-01

Cervical spinal cord injury can disrupt connections between the brain respiratory network and the respiratory muscles which can lead to partial or complete loss of ventilatory control and require ventilatory assistance. Unlike current open-loop technology, a closed-loop diaphragmatic pacing system could overcome the drawbacks of manual titration as well as respond to changing ventilation requirements. We present an original bio-inspired assistive technology for real-time ventilation assistance, implemented in a digital configurable Field Programmable Gate Array (FPGA). The bio-inspired controller, which is a spiking neural network (SNN) inspired by the medullary respiratory network, is as robust as a classic controller while having a flexible, low-power and low-cost hardware design. The system was simulated in MATLAB with FPGA-specific constraints and tested with a computational model of rat breathing; the model reproduced experimentally collected respiratory data in eupneic animals. The open-loop version of the bio-inspired controller was implemented on the FPGA. Electrical test bench characterizations confirmed the system functionality. Open and closed-loop paradigm simulations were simulated to test the FPGA system real-time behavior using the rat computational model. The closed-loop system monitors breathing and changes in respiratory demands to drive diaphragmatic stimulation. The simulated results inform future acute animal experiments and constitute the first step toward the development of a neuromorphic, adaptive, compact, low-power, implantable device. The bio-inspired hardware design optimizes the FPGA resource and time costs while harnessing the computational power of spike-based neuromorphic hardware. Its real-time feature makes it suitable for in vivo applications. PMID:27378844

Closed-loop adaptive optic comparison between a Shack-Hartmann and a distorted grating wavefront sensor

NASA Astrophysics Data System (ADS)

Harrison, Paul; Erry, Gavin R. G.; Otten, Leonard J.; Cuevas, Desirae M.; Weaver, Lawrence D.

2004-11-01

Earlier research reported a comparison of the wavefronts recorded simultaneously by a Shack-Hartmann and a Distorted Grating Wavefront Sensor (DGWFS). In this paper we present the results of a continuation of this earlier work where we have now closed an adaptive optics loop under simulated propagation conditions using the Advanced Concept Laboratory (ACL) at Lincoln Laboratory. For these measurements only one wavefront sensor controlled the deformable mirror at a time. To make direct comparisons between the sensors we took advantage of the ACL's ability to exactly replicate a time varying propagation simulation. Time varying and static comparisons of the two sensors controlling the ACL adaptive system under conditions that ranged from a benign path, D/r0 = 2, to a propagation condition with significant scintillation, D/r0 =9, will be shown using the corrected far field spot as a measure of performance. The paper includes a description of the DGWFS used for these tests and describes the procedure used to align and calibrate the sensor.

Closed-loop adaptive optic comparison between a Shack-Hartmann and a distorted-grating wavefront sensor

NASA Astrophysics Data System (ADS)

Harrison, Paul; Erry, Gavin R. G.; Otten, Leonard J., III; Cuevas, D. M.; Weaver, Lawrence D.

2004-02-01

Earlier research reported a comparison of the wavefronts recorded simultaneously by a Shack-Hartmann and a Distorted Grating Wavefront Sensor (DGWFS). In this paper we present the results of a continuation of this earlier work where we have now closed an adaptive optics loop under simulated propagation conditions using the Advanced Concept Laboratory (ACL) at Lincoln Laboratory. For these measurements only one wavefront sensor controlled the deformable mirror at a time. To make direct comparisons between the sensors we took advantage of the ACL"s ability to exactly replicate a time varying propagation simulation. Time varying and static comparisons of the two sensors controlling the ACL adaptive system under conditions that ranged from a benign path, D/r0 = 2, to a propagation condition with significant scintillation, D/r0 =9, will be shown using the corrected far field spot as a measure of performance. The paper includes a description of the DGWFS used for these tests and describes the procedure used to align and calibrate the sensor.

Application of higher harmonic blade feathering on the OH-6A helicopter for vibration reduction

NASA Technical Reports Server (NTRS)

Straub, F. K.; Byrns, E. V., Jr.

1986-01-01

The design, implementation, and flight test results of higher harmonic blade feathering for vibration reduction on the OH-6A helicopter are described. The higher harmonic control (HHC) system superimposes fourth harmonic inputs upon the stationary swashplate. These inputs are transformed into 3P, 4P and 5P blade feathering angles. This results in modified blade loads and reduced fuselage vibrations. The primary elements of this adaptive vibration suppression system are: (1) acceleration transducers sensing the vibratory response of the fuselage; (2) a higher harmonic blade pitch actuator system; (3) a flightworthy microcomputer, incorporating the algorithm for reducing vibrations, and (4) a signal conditioning system, interfacing between the sensors, the microcomputer and the HHC actuators. The program consisted of three distinct phases. First, the HHC system was designed and implemented on the MDHC OH-6A helicopter. Then, the open loop, or manual controlled, flight tests were performed, and finally, the closed loop adaptive control system was tested. In 1983, one portion of the closed loop testing was performed, and in 1984, additional closed loop tests were conducted with improved software. With the HHC system engaged, the 4P pilot seat vibration levels were significantly lower than the baseline ON-6A levels. Moreover, the system did not adversely affect blade loads or helicopter performance. In conclusion, this successful proof of concept project demonstrated HHC to be a viable vibration suppression mechanism.

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation.

PubMed

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2013-09-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro .

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation

PubMed Central

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2014-01-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro. PMID:24678126

A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Weissman, Alexander

2006-01-01

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…

Detection of no-model input-output pairs in closed-loop systems.

PubMed

Potts, Alain Segundo; Alvarado, Christiam Segundo Morales; Garcia, Claudio

2017-11-01

The detection of no-model input-output (IO) pairs is important because it can speed up the multivariable system identification process, since all the pairs with null transfer functions are previously discarded and it can also improve the identified model quality, thus improving the performance of model based controllers. In the available literature, the methods focus just on the open-loop case, since in this case there is not the effect of the controller forcing the main diagonal in the transfer matrix to one and all the other terms to zero. In this paper, a modification of a previous method able to detect no-model IO pairs in open-loop systems is presented, but adapted to perform this duty in closed-loop systems. Tests are performed by using the traditional methods and the proposed one to show its effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Feedback control methods for drug dosage optimisation. Concepts, classification and clinical application.

PubMed

Vozeh, S; Steimer, J L

1985-01-01

The concept of feedback control methods for drug dosage optimisation is described from the viewpoint of control theory. The control system consists of 5 parts: (a) patient (the controlled process); (b) response (the measured feedback); (c) model (the mathematical description of the process); (d) adaptor (to update the parameters); and (e) controller (to determine optimum dosing strategy). In addition to the conventional distinction between open-loop and closed-loop control systems, a classification is proposed for dosage optimisation techniques which distinguishes between tight-loop and loose-loop methods depending on whether physician's interaction is absent or included as part of the control step. Unlike engineering problems where the process can usually be controlled by fully automated devices, therapeutic situations often require that the physician be included in the decision-making process to determine the 'optimal' dosing strategy. Tight-loop and loose-loop methods can be further divided into adaptive and non-adaptive, depending on the presence of the adaptor. The main application areas of tight-loop feedback control methods are general anaesthesia, control of blood pressure, and insulin delivery devices. Loose-loop feedback methods have been used for oral anticoagulation and in therapeutic drug monitoring. The methodology, advantages and limitations of the different approaches are reviewed. A general feature common to all application areas could be observed: to perform well under routine clinical conditions, which are characterised by large interpatient variability and sometimes also intrapatient changes, control systems should be adaptive. Apart from application in routine drug treatment, feedback control methods represent an important research tool. They can be applied for the investigation of pathophysiological and pharmacodynamic processes. A most promising application is the evaluation of the relationship between an intermediate response (e.g. drug level), which is often used as feedback for dosage adjustment, and the final therapeutic goal.

Adaptation of a modern medium helicopter (Sikorsky S-76) to higher harmonic control

NASA Technical Reports Server (NTRS)

Oleary, J. J.; Kottapalli, S. B. R.; Davis, M. W.

1985-01-01

Sikorsky Aircraft has performed analytical studies, design analyses, and risk reduction tests have been performed for Higher Harmonic Control (HHC) on the S-76. The S-76 is an 8 to 10,000 lb helicopter which cruises at 145 kts. Flight test hardware has been assembled, main servo frequency response tested and upgraded, aircraft control system shake tested and verified, open loop controllers designed and fabricated, closed loop controllers defined and evaluated, and rotors turning ground and flight tests planned for the near future. Open loop analysis shows that about 2 deg of higher harmonic feathering at the blade 75% radius will be required to eliminate 4P vibration in the cockpit.

Robustness of reduced-order multivariable state-space self-tuning controller

NASA Technical Reports Server (NTRS)

Yuan, Zhuzhi; Chen, Zengqiang

1994-01-01

In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

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.

Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.

PubMed

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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Controls for space structures

NASA Astrophysics Data System (ADS)

Balas, Mark

1991-11-01

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

Controls for space structures

NASA Technical Reports Server (NTRS)

Balas, Mark

1991-01-01

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

Real-Time Adaptive Control of a Magnetic Levitation System with a Large Range of Load Disturbance.

PubMed

Zhang, Zhizhou; Li, Xiaolong

2018-05-11

In an idle light-load or a full-load condition, the change of the load mass of a suspension system is very significant. If the control parameters of conventional control methods remain unchanged, the suspension performance of the control system deteriorates rapidly or even loses stability when the load mass changes in a large range. In this paper, a real-time adaptive control method for a magnetic levitation system with large range of mass changes is proposed. First, the suspension control system model of the maglev train is built up, and the stability of the closed-loop system is analyzed. Then, a fast inner current-loop is used to simplify the design of the suspension control system, and an adaptive control method is put forward to ensure that the system is still in a stable state when the load mass varies in a wide range. Simulations and experiments show that when the load mass of the maglev system varies greatly, the adaptive control method is effective to suspend the system stably with a given displacement.

Real-Time Adaptive Control of a Magnetic Levitation System with a Large Range of Load Disturbance

PubMed Central

Zhang, Zhizhou; Li, Xiaolong

2018-01-01

In an idle light-load or a full-load condition, the change of the load mass of a suspension system is very significant. If the control parameters of conventional control methods remain unchanged, the suspension performance of the control system deteriorates rapidly or even loses stability when the load mass changes in a large range. In this paper, a real-time adaptive control method for a magnetic levitation system with large range of mass changes is proposed. First, the suspension control system model of the maglev train is built up, and the stability of the closed-loop system is analyzed. Then, a fast inner current-loop is used to simplify the design of the suspension control system, and an adaptive control method is put forward to ensure that the system is still in a stable state when the load mass varies in a wide range. Simulations and experiments show that when the load mass of the maglev system varies greatly, the adaptive control method is effective to suspend the system stably with a given displacement. PMID:29751610

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 encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching this goal.

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 approaches. Radiation tolerant FPGA's are a feasible option for reaching this goal.

Performance characteristics of an adaptive controller based on least-mean-square filters

NASA Technical Reports Server (NTRS)

Mehta, Rajiv S.; Merhav, Shmuel J.

1986-01-01

A closed loop, adaptive control scheme that uses a least mean square filter as the controller model is presented, along with simulation results that demonstrate the excellent robustness of this scheme. It is shown that the scheme adapts very well to unknown plants, even those that are marginally stable, responds appropriately to changes in plant parameters, and is not unduly affected by additive noise. A heuristic argument for the conditions necessary for convergence is presented. Potential applications and extensions of the scheme are also discussed.

Pulsatile desynchronizing delayed feedback for closed-loop deep brain stimulation

PubMed Central

Lysyansky, Borys; Rosenblum, Michael; Pikovsky, Arkady; Tass, Peter A.

2017-01-01

High-frequency (HF) deep brain stimulation (DBS) is the gold standard for the treatment of medically refractory movement disorders like Parkinson’s disease, essential tremor, and dystonia, with a significant potential for application to other neurological diseases. The standard setup of HF DBS utilizes an open-loop stimulation protocol, where a permanent HF electrical pulse train is administered to the brain target areas irrespectively of the ongoing neuronal dynamics. Recent experimental and clinical studies demonstrate that a closed-loop, adaptive DBS might be superior to the open-loop setup. We here combine the notion of the adaptive high-frequency stimulation approach, that aims at delivering stimulation adapted to the extent of appropriately detected biomarkers, with specifically desynchronizing stimulation protocols. To this end, we extend the delayed feedback stimulation methods, which are intrinsically closed-loop techniques and specifically designed to desynchronize abnormal neuronal synchronization, to pulsatile electrical brain stimulation. We show that permanent pulsatile high-frequency stimulation subjected to an amplitude modulation by linear or nonlinear delayed feedback methods can effectively and robustly desynchronize a STN-GPe network of model neurons and suggest this approach for desynchronizing closed-loop DBS. PMID:28273176

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.

Tonic accommodation predicts closed-loop accommodation responses.

PubMed

Liu, Chunming; Drew, Stefanie A; Borsting, Eric; Escobar, Amy; Stark, Lawrence; Chase, Christopher

2016-12-01

The purpose of this study is to examine the potential relationship between tonic accommodation (TA), near work induced TA-adaptation and the steady state closed-loop accommodation response (AR). Forty-two graduate students participated in the study. Various aspects of their accommodation system were objectively measured using an open-field infrared auto-refractor (Grand Seiko WAM-5500). Tonic accommodation was assessed in a completely dark environment. The association between TA and closed-loop AR was assessed using linear regression correlations and t-test comparisons. Initial mean baseline TA was 1.84diopter (D) (SD±1.29D) with a wide distribution range (-0.43D to 5.14D). For monocular visual tasks, baseline TA was significantly correlated with the closed-loop AR. The slope of the best fit line indicated that closed-loop AR varied by approximately 0.3D for every 1D change in TA. This ratio was consistent across a variety of viewing distances and different near work tasks, including both static targets and continuous reading. Binocular reading conditions weakened the correlation between baseline TA and AR, although results remained statistically significant. The 10min near reading task with a 3D demand did not reveal significant near work induced TA-adaptation for either monocular or binocular conditions. Consistently, the TA-adaptation did not show any correlation with AR during reading. This study found a strong association between open-loop TA and closed-loop AR across a variety of viewing distances and different near work tasks. Difference between the correlations under monocular and binocular reading condition suggests a potential role for vergence compensation during binocular closed-loop AR. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dual-thread parallel control strategy for ophthalmic adaptive optics.

PubMed

Yu, Yongxin; Zhang, Yuhua

To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a closed loop updating frequency up to 110 Hz, and demonstrated robust compensation for ocular wave aberration up to 50 Hz in an adaptive optics scanning laser ophthalmoscope.

Dual-thread parallel control strategy for ophthalmic adaptive optics

PubMed Central

Yu, Yongxin; Zhang, Yuhua

2015-01-01

To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a closed loop updating frequency up to 110 Hz, and demonstrated robust compensation for ocular wave aberration up to 50 Hz in an adaptive optics scanning laser ophthalmoscope. PMID:25866498

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

PubMed Central

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

Adaptive hybrid optimal quantum control for imprecisely characterized systems.

PubMed

Egger, D J; Wilhelm, F K

2014-06-20

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

Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

PubMed

Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

2011-04-01

This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

Sliding-mode control combined with improved adaptive feedforward for wafer scanner

NASA Astrophysics Data System (ADS)

Li, Xiaojie; Wang, Yiguang

2018-03-01

In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

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

NASA Technical Reports Server (NTRS)

Wen, John T.; Bayard, David S.

1988-01-01

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

Chemically controlled closed-loop insulin delivery.

PubMed

Ravaine, Valérie; Ancla, Christophe; Catargi, Bogdan

2008-11-24

Alternative treatments for diabetes are currently being investigated to improve both patient comfort and avoid complications due to hyperglycaemia episodes. In the absence of a cure like pancreas or beta-islets transplants, the ideal method would be an artificial "closed-loop" system able to mimic pancreas activity. This would operate continuously and automatically, causing appropriate response to losses and gains in glucose levels. Chemically controlled closed-loop insulin delivery has been explored by two main strategies. The first one consists in delivering insulin with a glucose-responsive matrix. Polymeric hydrogels that swell or shrink according to the glucose concentration allow delivering insulin doses adapted to the glucose concentration. The second strategy consists in modifying insulin itself with glucose-sensitive functional groups that trigger its activity. Recent developments made in these areas represent significant progress in terms of biocompatibility, selectivity, pharmacokinetics, and easiness of administration, as required for in vivo applications. Although some issues still have to be overcome, this field of research is promising as a possible alternative to other approaches for diabetes treatment.

Bioelectric Control of a 757 Class High Fidelity Aircraft Simulation

NASA Technical Reports Server (NTRS)

Jorgensen, Charles; Wheeler, Kevin; Stepniewski, Slawomir; Norvig, Peter (Technical Monitor)

2000-01-01

This paper presents results of a recent experiment in fine grain Electromyographic (EMG) signal recognition, We demonstrate bioelectric flight control of 757 class simulation aircraft landing at San Francisco International Airport. The physical instrumentality of a pilot control stick is not used. A pilot closes a fist in empty air and performs control movements which are captured by a dry electrode array on the arm, analyzed and routed through a flight director permitting full pilot outer loop control of the simulation. A Vision Dome immersive display is used to create a VR world for the aircraft body mechanics and flight changes to pilot movements. Inner loop surfaces and differential aircraft thrust is controlled using a hybrid neural network architecture that combines a damage adaptive controller (Jorgensen 1998, Totah 1998) with a propulsion only based control system (Bull & Kaneshige 1997). Thus the 757 aircraft is not only being flown bioelectrically at the pilot level but also demonstrates damage adaptive neural network control permitting adaptation to severe changes in the physical flight characteristics of the aircraft at the inner loop level. To compensate for accident scenarios, the aircraft uses remaining control surface authority and differential thrust from the engines. To the best of our knowledge this is the first time real time bioelectric fine-grained control, differential thrust based control, and neural network damage adaptive control have been integrated into a single flight demonstration. The paper describes the EMG pattern recognition system and the bioelectric pattern recognition methodology.

Closed-Loop Control Better than Open-Loop Control of Profofol TCI Guided by BIS: A Randomized, Controlled, Multicenter Clinical Trial to Evaluate the CONCERT-CL Closed-Loop System

PubMed Central

Zhang, Xuena; Wu, Anshi; Yao, Shanglong; Xue, Zhanggang; Yue, Yun

2015-01-01

Background The CONCERT-CL closed-loop infusion system designed by VERYARK Technology Co., Ltd. (Guangxi, China) is an innovation using TCI combined with closed-loop controlled intravenous anesthesia under the guide of BIS. In this study we performed a randomized, controlled, multicenter study to compare closed-loop control and open-loop control of propofol by using the CONCERT-CL closed-loop infusion system. Methods 180 surgical patients from three medical centers undergone TCI intravenous anesthesia with propofol and remifentanil were randomly assigned to propofol closed-loop group and propofol opened-loop groups. Primary outcome was global score (GS, GS = (MDAPE+Wobble)/% of time of bispectral index (BIS) 40-60). Secondary outcomes were doses of the anesthetics and emergence time from anesthesia, such as, time to tracheal extubation. Results There were 89 and 86 patients in the closed-loop and opened-loop groups, respectively. GS in the closed-loop groups (22.21±8.50) were lower than that in the opened-loop group (27.19±15.26) (p=0.009). The higher proportion of time of BIS between 40 and 60 was also observed in the closed-loop group (84.11±9.50%), while that was 79.92±13.17% in the opened-loop group, (p=0.016). No significant differences in propofol dose and time of tracheal extubation were observed. The frequency of propofol regulation in the closed-loop group (31.55±9.46 times/hr) was obverse higher than that in the opened-loop group (6.84±6.21 times/hr) (p=0.000). Conclusion The CONCERT-CL closed-loop infusion system can automatically regulate the TCI of propofol, maintain the BIS value in an adequate range and reduce the workload of anesthesiologists better than open-loop system. Trial Registration ChiCTR ChiCTR-OOR-14005551 PMID:25886041

Robustly stable adaptive control of a tandem of master-slave robotic manipulators with force reflection by using a multiestimation scheme.

PubMed

Ibeas, Asier; de la Sen, Manuel

2006-10-01

The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.

System identification from closed-loop data with known output feedback dynamics

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Horta, Lucas G.; Longman, Richard W.

1992-01-01

This paper presents a procedure to identify the open loop systems when it is operating under closed loop conditions. First, closed loop excitation data are used to compute the system open loop and closed loop Markov parameters. The Markov parameters, which are the pulse response samples, are then used to compute a state space representation of the open loop system. Two closed loop configurations are considered in this paper. The closed loop system can have either a linear output feedback controller or a dynamic output feedback controller. Numerical examples are provided to illustrate the proposed closed loop identification method.

Adaptive Formation Control of Electrically Driven Nonholonomic Mobile Robots With Limited Information.

PubMed

Bong Seok Park; Jin Bae Park; Yoon Ho Choi

2011-08-01

We present a leader-follower-based adaptive formation control method for electrically driven nonholonomic mobile robots with limited information. First, an adaptive observer is developed under the condition that the velocity measurement is not available. With the proposed adaptive observer, the formation control part is designed to achieve the desired formation and guarantee the collision avoidance. In addition, neural network is employed to compensate the actuator saturation, and the projection algorithm is used to estimate the velocity information of the leader. It is shown, by using the Lyapunov theory, that all errors of the closed-loop system are uniformly ultimately bounded. Simulation results are presented to illustrate the performance of the proposed control system.

Results of adaptive feedforward on GTA

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

Ziomek, C.D.; Denney, P.M.; Regan, A.H.

1993-01-01

This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients andmore » phase droop in the klystron amplifier.« less

Results of adaptive feedforward on GTA

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

Ziomek, C.D.; Denney, P.M.; Regan, A.H.

1993-06-01

This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients andmore » phase droop in the klystron amplifier.« less

Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.

PubMed

Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong

2013-12-01

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Dual-loop model of the human controller

NASA Technical Reports Server (NTRS)

Hess, R. A.

1978-01-01

A dual-loop model of the human controller in single-axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure that involves feeding back that portion of controlled element output rate that is due to control activity. A novel feature of the model is the explicit appearance of the human's internal representation of the manipulator-controlled element dynamics in the inner loop. The sensor inputs to the human controller are assumed to be system error and control force. The former can be sensed via visual, aural, or tactile displays, whereas the latter is assumed to be sensed in kinesthetic fashion. A set of general adaptive characteristics for the model is hypothesized, including a method for selecting simplified internal models of the manipulator-controlled element dynamics. It is demonstrated that the model can produce controller describing functions that closely approximate those measured in four laboratory tracking tasks in which the controlled element dynamics vary considerably in terms of ease of control. An empirically derived expression for the normalized injected error remnant spectrum is introduced.

Theoretical linear approach to the combined man-manipulator system in manual control of an aircraft

NASA Technical Reports Server (NTRS)

Brauser, K.

1981-01-01

An approach to the calculation of the dynamic characteristics of the combined man manipulator system in manual aircraft control was derived from a model of the neuromuscular system. This model combines the neuromuscular properties of man with the physical properties of the manipulator system which is introduced as pilot manipulator model into the manual aircraft control. The assumption of man as a quasilinear and time invariant control operator adapted to operating states, depending on the flight phases, of the control system gives rise to interesting solutions of the frequency domain transfer functions of both the man manipulator system and the closed loop pilot aircraft control system. It is shown that it is necessary to introduce the complete precision pilot manipulator model into the closed loop pilot aircraft transfer function in order to understand the well known handling quality criteria, and to derive these criteria directly from human operator properties.

An application of modern control theory to jet propulsion systems. [considering onboard computer

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1975-01-01

The control of an airbreathing turbojet engine by an onboard digital computer is studied. The approach taken is to model the turbojet engine as a linear, multivariable system whose parameters vary with engine operating environment. From this model adaptive closed-loop or feedback control laws are designed and applied to the acceleration of the turbojet engine.

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.

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.

Modeling and closed-loop control of hypnosis by means of bispectral index (BIS) with isoflurane.

PubMed

Gentilini, A; Rossoni-Gerosa, M; Frei, C W; Wymann, R; Morari, M; Zbinden, A M; Schnider, T W

2001-08-01

A model-based closed-loop control system is presented to regulate hypnosis with the volatile anesthetic isoflurane. Hypnosis is assessed by means of the bispectral index (BIS), a processed parameter derived from the electroencephalogram. Isoflurane is administered through a closed-circuit respiratory system. The model for control was identified on a population of 20 healthy volunteers. It consists of three parts: a model for the respiratory system, a pharmacokinetic model and a pharmacodynamic model to predict BIS at the effect compartment. A cascaded internal model controller is employed. The master controller compares the actual BIS and the reference value set by the anesthesiologist and provides expired isoflurane concentration references to the slave controller. The slave controller maneuvers the fresh gas anesthetic concentration entering the respiratory system. The controller is designed to adapt to different respiratory conditions. Anti-windup measures protect against performance degradation in the event of saturation of the input signal. Fault detection schemes in the controller cope with BIS and expired concentration measurement artifacts. The results of clinical studies on humans are presented.

Closed-loop focal plane wavefront control with the SCExAO instrument

NASA Astrophysics Data System (ADS)

Martinache, Frantz; Jovanovic, Nemanja; Guyon, Olivier

2016-09-01

Aims: This article describes the implementation of a focal plane based wavefront control loop on the high-contrast imaging instrument SCExAO (Subaru Coronagraphic Extreme Adaptive Optics). The sensor relies on the Fourier analysis of conventional focal-plane images acquired after an asymmetric mask is introduced in the pupil of the instrument. Methods: This absolute sensor is used here in a closed-loop to compensate for the non-common path errors that normally affects any imaging system relying on an upstream adaptive optics system.This specific implementation was used to control low-order modes corresponding to eight zernike modes (from focus to spherical). Results: This loop was successfully run on-sky at the Subaru Telescope and is used to offset the SCExAO deformable mirror shape used as a zero-point by the high-order wavefront sensor. The paper details the range of errors this wavefront-sensing approach can operate within and explores the impact of saturation of the data and how it can be bypassed, at a cost in performance. Conclusions: Beyond this application, because of its low hardware impact, the asymmetric pupil Fourier wavefront sensor (APF-WFS) can easily be ported in a wide variety of wavefront sensing contexts, for ground- as well space-borne telescopes, and for telescope pupils that can be continuous, segmented or even sparse. The technique is powerful because it measures the wavefront where it really matters, at the level of the science detector.

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

PubMed

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

An Adaptive Control Technology for Safety of a GTM-like Aircraft

NASA Technical Reports Server (NTRS)

Matsutani, Megumi; Crespo, Luis G.; Annaswamy, Anuradha; Jang, Jinho

2010-01-01

An adaptive control architecture for safe performance of a transport aircraft subject to various adverse conditions is proposed and verified in this report. This architecture combines a nominal controller based on a Linear Quadratic Regulator with integral action, and an adaptive controller that accommodates actuator saturation and bounded disturbances. The effectiveness of the baseline controller and its adaptive augmentation are evaluated using a stand-alone control veri fication methodology. Case studies that pair individual parameter uncertainties with critical flight maneuvers are studied. The resilience of the controllers is determined by evaluating the degradation in closed-loop performance resulting from increasingly larger deviations in the uncertain parameters from their nominal values. Symmetric and asymmetric actuator failures, flight upsets, and center of gravity displacements, are some of the uncertainties considered.

Adaptive PID formation control of nonholonomic robots without leader's velocity information.

PubMed

Shen, Dongbin; Sun, Weijie; Sun, Zhendong

2014-03-01

This paper proposes an adaptive proportional integral derivative (PID) algorithm to solve a formation control problem in the leader-follower framework where the leader robot's velocities are unknown for the follower robots. The main idea is first to design some proper ideal control law for the formation system to obtain a required performance, and then to propose the adaptive PID methodology to approach the ideal controller. As a result, the formation is achieved with much more enhanced robust formation performance. The stability of the closed-loop system is theoretically proved by Lyapunov method. Both numerical simulations and physical vehicle experiments are presented to verify the effectiveness of the proposed adaptive PID algorithm. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Integrated model reference adaptive control and time-varying angular rate estimation for micro-machined gyroscopes

NASA Astrophysics Data System (ADS)

Tsai, Nan-Chyuan; Sue, Chung-Yang

2010-02-01

Owing to the imposed but undesired accelerations such as quadrature error and cross-axis perturbation, the micro-machined gyroscope would not be unconditionally retained at resonant mode. Once the preset resonance is not sustained, the performance of the micro-gyroscope is accordingly degraded. In this article, a direct model reference adaptive control loop which is integrated with a modified disturbance estimating observer (MDEO) is proposed to guarantee the resonant oscillations at drive mode and counterbalance the undesired disturbance mainly caused by quadrature error and cross-axis perturbation. The parameters of controller are on-line innovated by the dynamic error between the MDEO output and expected response. In addition, Lyapunov stability theory is employed to examine the stability of the closed-loop control system. Finally, the efficacy of numerical evaluation on the exerted time-varying angular rate, which is to be detected and measured by the gyroscope, is verified by intensive simulations.

Adaptive tracking control for a class of stochastic switched systems

NASA Astrophysics Data System (ADS)

Zhang, Hui; Xia, Yuanqing

2018-02-01

The problem of adaptive tracking is considered for a class of stochastic switched systems, in this paper. As preliminaries, the criterion of global asymptotical practical stability in probability is first presented by the aid of common Lyapunov function method. Based on the Lyapunov stability criterion, adaptive backstepping controllers are designed to guarantee that the closed-loop system has a unique global solution, which is globally asymptotically practically stable in probability, and the tracking error in the fourth moment converges to an arbitrarily small neighbourhood of zero. Simulation examples are given to demonstrate the efficiency of the proposed schemes.

Application of adaptive antenna techniques to future commercial satellite communication

NASA Technical Reports Server (NTRS)

Ersoy, L.; Lee, E. A.; Matthews, E. W.

1987-01-01

The purpose of this contract was to identify the application of adaptive antenna technique in future operational commercial satellite communication systems and to quantify potential benefits. The contract consisted of two major subtasks. Task 1, Assessment of Future Commercial Satellite System Requirements, was generally referred to as the Adaptive section. Task 2 dealt with Pointing Error Compensation Study for a Multiple Scanning/Fixed Spot Beam Reflector Antenna System and was referred to as the reconfigurable system. Each of these tasks was further sub-divided into smaller subtasks. It should also be noted that the reconfigurable system is usually defined as an open-loop system while the adaptive system is a closed-loop system. The differences between the open- and closed-loop systems were defined. Both the adaptive and reconfigurable systems were explained and the potential applications of such systems were presented in the context of commercial communication satellite systems.

Application of adaptive antenna techniques to future commercial satellite communications. Executive summary

NASA Technical Reports Server (NTRS)

Ersoy, L.; Lee, E. A.; Matthews, E. W.

1987-01-01

The purpose of this contract was to identify the application of adaptive antenna technique in future operational commercial satellite communication systems and to quantify potential benefits. The contract consisted of two major subtasks. Task 1, Assessment of Future Commercial Satellite System Requirements, was generally referred to as the Adaptive section. Task 2 dealt with Pointing Error Compensation Study for a Multiple Scanning/Fixed Spot Beam Reflector Antenna System and was referred to as the reconfigurable system. Each of these tasks was further subdivided into smaller subtasks. It should also be noted that the reconfigurable system is usually defined as an open-loop system while the adaptive system is a closed-loop system. The differences between the open- and closed-loop systems were defined. Both the adaptive and reconfigurable systems were explained and the potential applications of such systems were presented in the context of commercial communication satellite systems.

Biocybernetic Control of Vigilance Task Parameters

NASA Technical Reports Server (NTRS)

Freeman, Frederick G.

2000-01-01

The major focus of the present proposal was to examine psychophysiological variables that are 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 the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both 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. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. 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 vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Fast spacecraft adaptive attitude tracking control through immersion and invariance design

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Adaptive support ventilation: State of the art review

PubMed Central

Fernández, Jaime; Miguelena, Dayra; Mulett, Hernando; Godoy, Javier; Martinón-Torres, Federico

2013-01-01

Mechanical ventilation is one of the most commonly applied interventions in intensive care units. Despite its life-saving role, it can be a risky procedure for the patient if not applied appropriately. To decrease risks, new ventilator modes continue to be developed in an attempt to improve patient outcomes. Advances in ventilator modes include closed-loop systems that facilitate ventilator manipulation of variables based on measured respiratory parameters. Adaptive support ventilation (ASV) is a positive pressure mode of mechanical ventilation that is closed-loop controlled, and automatically adjust based on the patient's requirements. In order to deliver safe and appropriate patient care, clinicians need to achieve a thorough understanding of this mode, including its effects on underlying respiratory mechanics. This article will discuss ASV while emphasizing appropriate ventilator settings, their advantages and disadvantages, their particular effects on oxygenation and ventilation, and the monitoring priorities for clinicians. PMID:23833471

Optimization of the open-loop liquid crystal adaptive optics retinal imaging system

NASA Astrophysics Data System (ADS)

Kong, Ningning; Li, Chao; Xia, Mingliang; Li, Dayu; Qi, Yue; Xuan, Li

2012-02-01

An open-loop adaptive optics (AO) system for retinal imaging was constructed using a liquid crystal spatial light modulator (LC-SLM) as the wavefront compensator. Due to the dispersion of the LC-SLM, there was only one illumination source for both aberration detection and retinal imaging in this system. To increase the field of view (FOV) for retinal imaging, a modified mechanical shutter was integrated into the illumination channel to control the size of the illumination spot on the fundus. The AO loop was operated in a pulsing mode, and the fundus was illuminated twice by two laser impulses in a single AO correction loop. As a result, the FOV for retinal imaging was increased to 1.7-deg without compromising the aberration detection accuracy. The correction precision of the open-loop AO system was evaluated in a closed-loop configuration; the residual error is approximately 0.0909λ (root-mean-square, RMS), and the Strehl ratio ranges to 0.7217. Two subjects with differing rates of myopia (-3D and -5D) were tested. High-resolution images of capillaries and photoreceptors were obtained.

Comparison of the Shack-Hartmann and plenoptic sensor in closed-loop adaptive optics system

NASA Astrophysics Data System (ADS)

Jiang, Pengzhi; Xu, Jieping; Liang, Yonghui; Mao, Hongjun

2016-03-01

The wavefront sensor is used in adaptive optics (AO) to detect the atmospheric distortion, which feeds back to the deformable mirror to compensate for this distortion. While the Shack-Hartmann sensor has been widely used, the plenoptic sensor was proposed in recent years. The two different wavefront sensing methods have different interpretations and numerical consequences, though they are both slope-based. The plenoptic sensor is compared with the Shack-Hartmann sensor in a closed-loop AO system. Simulations are performed to investigate their performances under closed-loop conditions. The plenoptic sensors both without and with modulation are discussed. The results show that the closed-loop performance of the plenoptic sensor without modulation is worse than that of the Shack-Hartmann sensor when the star for observation is brighter than magnitude 7, but better when the star is fainter. The closed-loop performance of the plenoptic sensor could be improved by modulation, except for the faint star. In summary, the limiting magnitude of the astronomical AO system may be improved by using the plenoptic sensor instead of the Shack-Hartmann sensor, and the modulation of the plenoptic sensor is more suitable for the bright star.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

PubMed

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

Experimental aeroelastic control using adaptive wing model concepts

NASA Astrophysics Data System (ADS)

Costa, Antonio P.; Moniz, Paulo A.; Suleman, Afzal

2001-06-01

The focus of this study is to evaluate the aeroelastic performance and control of adaptive wings. Ailerons and flaps have been designed and implemented into 3D wings for comparison with adaptive structures and active aerodynamic surface control methods. The adaptive structures concept, the experimental setup and the control design are presented. The wind-tunnel tests of the wing models are presented for the open- and closed-loop systems. The wind tunnel testing has allowed for quantifying the effectiveness of the piezoelectric vibration control of the wings, and also provided performance data for comparison with conventional aerodynamic control surfaces. The results indicate that a wing utilizing skins as active structural elements with embedded piezoelectric actuators can be effectively used to improve the aeroelastic response of aeronautical components. It was also observed that the control authority of adaptive wings is much greater than wings using conventional aerodynamic control surfaces.

Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

PubMed

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. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Zhang, Huaguang; Lin, Chong

2016-01-01

This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics.

PubMed

Li, Yongming; Sui, Shuai; Tong, Shaocheng

2017-02-01

This paper deals with the problem of adaptive fuzzy output feedback control for a class of stochastic nonlinear switched systems. The controlled system in this paper possesses unmeasured states, completely unknown nonlinear system functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on the switching signal is constructed to tackle the unmeasured states. Fuzzy logic systems are employed to identify the completely unknown nonlinear system functions. Based on the common Lyapunov stability theory and stochastic small-gain theorem, a new robust adaptive fuzzy backstepping stabilization control strategy is developed. The stability of the closed-loop system on input-state-practically stable in probability is proved. The simulation results are given to verify the efficiency of the proposed fuzzy adaptive control scheme.

Multivariable adaptive closed-loop control of an artificial pancreas without meal and activity announcement.

PubMed

Turksoy, Kamuran; Bayrak, Elif Seyma; Quinn, Lauretta; Littlejohn, Elizabeth; Cinar, Ali

2013-05-01

Accurate closed-loop control is essential for developing artificial pancreas (AP) systems that adjust insulin infusion rates from insulin pumps. Glucose concentration information from continuous glucose monitoring (CGM) systems is the most important information for the control system. Additional physiological measurements can provide valuable information that can enhance the accuracy of the control system. Proportional-integral-derivative control and model predictive control have been popular in AP development. Their implementations to date rely on meal announcements (e.g., bolus insulin dose based on insulin:carbohydrate ratios) by the user. Adaptive control techniques provide a powerful alternative that do not necessitate any meal or activity announcements. Adaptive control systems based on the generalized predictive control framework are developed by extending the recursive modeling techniques. Physiological signals such as energy expenditure and galvanic skin response are used along with glucose measurements to generate a multiple-input-single-output model for predicting future glucose concentrations used by the controller. Insulin-on-board (IOB) is also estimated and used in control decisions. The controllers were tested with clinical studies that include seven cases with three different patients with type 1 diabetes for 32 or 60 h without any meal or activity announcements. The adaptive control system kept glucose concentration in the normal preprandial and postprandial range (70-180 mg/dL) without any meal or activity announcements during the test period. After IOB estimation was added to the control system, mild hypoglycemic episodes were observed only in one of the four experiments. This was reflected in a plasma glucose value of 56 mg/dL (YSI 2300 STAT; Yellow Springs Instrument, Yellow Springs, OH) and a CGM value of 63 mg/dL). Regulation of blood glucose concentration with an AP using adaptive control techniques was successful in clinical studies, even without any meal and physical activity announcement.

Decentralized adaptive control of interconnected nonlinear systems with unknown control directions.

PubMed

Huang, Jiangshuai; Wang, Qing-Guo

2018-03-01

In this paper, we propose a decentralized adaptive control scheme for a class of interconnected strict-feedback nonlinear systems without a priori knowledge of subsystems' control directions. To address this problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifying the interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in a single inequality. Global stability of the closed-loop system and asymptotic stabilization of subsystems' output are proved and a simulation example is given to illustrate the effectiveness of the proposed control scheme. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

PubMed

Bagherpoor, H M; Salmasi, Farzad R

2015-07-01

In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

PubMed

Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

2017-07-01

In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

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

PubMed

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

2017-07-01

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

Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

PubMed

Chen, Tien-Chi; Yu, Chih-Hsien

2009-07-01

A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2006-12-01

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

PubMed

Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

2017-07-01

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

Iterative LQG Controller Design Through Closed-Loop Identification

NASA Technical Reports Server (NTRS)

Hsiao, Min-Hung; Huang, Jen-Kuang; Cox, David E.

1996-01-01

This paper presents an iterative Linear Quadratic Gaussian (LQG) controller design approach for a linear stochastic system with an uncertain open-loop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQC controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

Bandwidth controller for phase-locked-loop

NASA Technical Reports Server (NTRS)

Brockman, Milton H. (Inventor)

1992-01-01

A phase locked loop utilizing digital techniques to control the closed loop bandwidth of the RF carrier phase locked loop in a receiver provides high sensitivity and a wide dynamic range for signal reception. After analog to digital conversion, a digital phase locked loop bandwidth controller provides phase error detection with automatic RF carrier closed loop tracking bandwidth control to accommodate several modes of transmission.

Stress inoculation training supported by physiology-driven adaptive virtual reality stimulation.

PubMed

Popović, Sinisa; Horvat, Marko; Kukolja, Davor; Dropuljić, Branimir; Cosić, Kresimir

2009-01-01

Significant proportion of psychological problems related to combat stress in recent large peacekeeping operations underscores importance of effective methods for strengthening the stress resistance of military personnel. Adaptive control of virtual reality (VR) stimulation, based on estimation of the subject's emotional state from physiological signals, may enhance existing stress inoculation training (SIT). Physiology-driven adaptive VR stimulation can tailor the progress of stressful stimuli delivery to the physiological characteristics of each individual, which is indicated for improvement in stress resistance. Therefore, following an overview of SIT and its applications in the military setting, generic concept of physiology-driven adaptive VR stimulation is presented in the paper. Toward the end of the paper, closed-loop adaptive control strategy applicable to SIT is outlined.

Diagonal dominance for the multivariable Nyquist array using function minimization

NASA Technical Reports Server (NTRS)

Leininger, G. G.

1977-01-01

A new technique for the design of multivariable control systems using the multivariable Nyquist array method was developed. A conjugate direction function minimization algorithm is utilized to achieve a diagonal dominant condition over the extended frequency range of the control system. The minimization is performed on the ratio of the moduli of the off-diagonal terms to the moduli of the diagonal terms of either the inverse or direct open loop transfer function matrix. Several new feedback design concepts were also developed, including: (1) dominance control parameters for each control loop; (2) compensator normalization to evaluate open loop conditions for alternative design configurations; and (3) an interaction index to determine the degree and type of system interaction when all feedback loops are closed simultaneously. This new design capability was implemented on an IBM 360/75 in a batch mode but can be easily adapted to an interactive computer facility. The method was applied to the Pratt and Whitney F100 turbofan engine.

Improved Controller for a Three-Axis Piezoelectric Stage

NASA Technical Reports Server (NTRS)

Rao, Shanti; Palmer, Dean

2009-01-01

An improved closed-loop controller has been built for a three-axis piezoelectric positioning stage. The stage can be any of a number of commercially available or custom-made units that are used for precise three-axis positioning of optics in astronomical instruments and could be used for precise positioning in diverse fields of endeavor that include adaptive optics, fabrication of semiconductors, and nanotechnology.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems.

PubMed

Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi

2018-01-01

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

A reconfigurable visual-programming library for real-time closed-loop cellular electrophysiology

PubMed Central

Biró, István; Giugliano, Michele

2015-01-01

Most of the software platforms for cellular electrophysiology are limited in terms of flexibility, hardware support, ease of use, or re-configuration and adaptation for non-expert users. Moreover, advanced experimental protocols requiring real-time closed-loop operation to investigate excitability, plasticity, dynamics, are largely inaccessible to users without moderate to substantial computer proficiency. Here we present an approach based on MATLAB/Simulink, exploiting the benefits of LEGO-like visual programming and configuration, combined to a small, but easily extendible library of functional software components. We provide and validate several examples, implementing conventional and more sophisticated experimental protocols such as dynamic-clamp or the combined use of intracellular and extracellular methods, involving closed-loop real-time control. The functionality of each of these examples is demonstrated with relevant experiments. These can be used as a starting point to create and support a larger variety of electrophysiological tools and methods, hopefully extending the range of default techniques and protocols currently employed in experimental labs across the world. PMID:26157385

Adaptive enhancement of learning protocol in hippocampal cultured networks grown on multielectrode arrays

PubMed Central

Pimashkin, Alexey; Gladkov, Arseniy; Mukhina, Irina; Kazantsev, Victor

2013-01-01

Learning in neuronal networks can be investigated using dissociated cultures on multielectrode arrays supplied with appropriate closed-loop stimulation. It was shown in previous studies that weakly respondent neurons on the electrodes can be trained to increase their evoked spiking rate within a predefined time window after the stimulus. Such neurons can be associated with weak synaptic connections in nearby culture network. The stimulation leads to the increase in the connectivity and in the response. However, it was not possible to perform the learning protocol for the neurons on electrodes with relatively strong synaptic inputs and responding at higher rates. We proposed an adaptive closed-loop stimulation protocol capable to achieve learning even for the highly respondent electrodes. It means that the culture network can reorganize appropriately its synaptic connectivity to generate a desired response. We introduced an adaptive reinforcement condition accounting for the response variability in control stimulation. It significantly enhanced the learning protocol to a large number of responding electrodes independently on its base response level. We also found that learning effect preserved after 4–6 h after training. PMID:23745105

A nonlinear control method based on ANFIS and multiple models for a class of SISO nonlinear systems and its application.

PubMed

Zhang, Yajun; Chai, Tianyou; Wang, Hong

2011-11-01

This paper presents a novel nonlinear control strategy for a class of uncertain single-input and single-output discrete-time nonlinear systems with unstable zero-dynamics. The proposed method combines adaptive-network-based fuzzy inference system (ANFIS) with multiple models, where a linear robust controller, an ANFIS-based nonlinear controller and a switching mechanism are integrated using multiple models technique. It has been shown that the linear controller can ensure the boundedness of the input and output signals and the nonlinear controller can improve the dynamic performance of the closed loop system. Moreover, it has also been shown that the use of the switching mechanism can simultaneously guarantee the closed loop stability and improve its performance. As a result, the controller has the following three outstanding features compared with existing control strategies. First, this method relaxes the assumption of commonly-used uniform boundedness on the unmodeled dynamics and thus enhances its applicability. Second, since ANFIS is used to estimate and compensate the effect caused by the unmodeled dynamics, the convergence rate of neural network learning has been increased. Third, a "one-to-one mapping" technique is adapted to guarantee the universal approximation property of ANFIS. The proposed controller is applied to a numerical example and a pulverizing process of an alumina sintering system, respectively, where its effectiveness has been justified.

The development of a closed-loop flight controller with panel method integration for gust alleviation using biomimetic feathers on aircraft wings

NASA Astrophysics Data System (ADS)

Blower, Christopher J.; Lee, Woody; Wickenheiser, Adam M.

2012-04-01

This paper presents the development of a biomimetic closed-loop flight controller that integrates gust alleviation and flight control into a single distributed system. Modern flight controllers predominantly rely on and respond to perturbations in the global states, resulting in rotation or displacement of the entire aircraft prior to the response. This bio-inspired gust alleviation system (GAS) employs active deflection of electromechanical feathers that react to changes in the airflow, i.e. the local states. The GAS design is a skeletal wing structure with a network of featherlike panels installed on the wing's surfaces, creating the airfoil profile and replacing the trailing-edge flaps. In this study, a dynamic model of the GAS-integrated wing is simulated to compute gust-induced disturbances. The system implements continuous adjustment to flap orientation to perform corrective responses to inbound gusts. MATLAB simulations, using a closed-loop LQR integrated with a 2D adaptive panel method, allow analysis of the morphing structure's aerodynamic data. Non-linear and linear dynamic models of the GAS are compared to a traditional single control surface baseline wing. The feedback loops synthesized rely on inertial changes in the global states; however, variations in number and location of feather actuation are compared. The bio-inspired system's distributed control effort allows the flight controller to interchange between the single and dual trailing edge flap profiles, thereby offering an improved efficiency to gust response in comparison to the traditional wing configuration. The introduction of aero-braking during continuous gusting flows offers a 25% reduction in x-velocity deviation; other flight parameters can be reduced in magnitude and deviation through control weighting optimization. Consequently, the GAS demonstrates enhancements to maneuverability and stability in turbulent intensive environments.

Combining Charge Couple Devices and Rate Sensors for the Feedforward Control System of a Charge Coupled Device Tracking Loop.

PubMed

Tang, Tao; Tian, Jing; Zhong, Daijun; Fu, Chengyu

2016-06-25

A rate feed forward control-based sensor fusion is proposed to improve the closed-loop performance for a charge couple device (CCD) tracking loop. The target trajectory is recovered by combining line of sight (LOS) errors from the CCD and the angular rate from a fiber-optic gyroscope (FOG). A Kalman filter based on the Singer acceleration model utilizes the reconstructive target trajectory to estimate the target velocity. Different from classical feed forward control, additive feedback loops are inevitably added to the original control loops due to the fact some closed-loop information is used. The transfer function of the Kalman filter in the frequency domain is built for analyzing the closed loop stability. The bandwidth of the Kalman filter is the major factor affecting the control stability and close-loop performance. Both simulations and experiments are provided to demonstrate the benefits of the proposed algorithm.

Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy

NASA Astrophysics Data System (ADS)

Sun, Yong-Zheng; Leng, Si-Yang; Lai, Ying-Cheng; Grebogi, Celso; Lin, Wei

2017-11-01

Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure. The closed-loop controller is tested on a large number of real systems including stem cell differentiation, food webs, random ecosystems, and spiking neuronal networks. Our results represent a step forward in developing a rigorous and general framework to control nonlinear dynamical networks with a complex topology.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

PubMed

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

PubMed Central

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J.; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. PMID:22666004

Plenoptic camera wavefront sensing with extended sources

NASA Astrophysics Data System (ADS)

Jiang, Pengzhi; Xu, Jieping; Liang, Yonghui; Mao, Hongjun

2016-09-01

The wavefront sensor is used in adaptive optics to detect the atmospheric distortion, which feeds back to the deformable mirror to compensate for this distortion. Different from the Shack-Hartmann sensor that has been widely used with point sources, the plenoptic camera wavefront sensor has been proposed as an alternative wavefront sensor adequate for extended objects in recent years. In this paper, the plenoptic camera wavefront sensing with extended sources is discussed systematically. Simulations are performed to investigate the wavefront measurement error and the closed-loop performance of the plenoptic sensor. The results show that there are an optimal lenslet size and an optimal number of pixels to make the best performance. The RMS of the resulting corrected wavefront in closed-loop adaptive optics system is less than 108 nm (0.2λ) when D/r0 ≤ 10 and the magnitude M ≤ 5. Our investigation indicates that the plenoptic sensor is efficient to operate on extended sources in the closed-loop adaptive optics system.

Enhancing the effectiveness of human-robot teaming with a closed-loop system.

PubMed

Teo, Grace; Reinerman-Jones, Lauren; Matthews, Gerald; Szalma, James; Jentsch, Florian; Hancock, Peter

2018-02-01

With technological developments in robotics and their increasing deployment, human-robot teams are set to be a mainstay in the future. To develop robots that possess teaming capabilities, such as being able to communicate implicitly, the present study implemented a closed-loop system. This system enabled the robot to provide adaptive aid without the need for explicit commands from the human teammate, through the use of multiple physiological workload measures. Such measures of workload vary in sensitivity and there is large inter-individual variability in physiological responses to imposed taskload. Workload models enacted via closed-loop system should accommodate such individual variability. The present research investigated the effects of the adaptive robot aid vs. imposed aid on performance and workload. Results showed that adaptive robot aid driven by an individualized workload model for physiological response resulted in greater improvements in performance compared to aid that was simply imposed by the system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probabilistic DHP adaptive critic for nonlinear stochastic control systems.

PubMed

Herzallah, Randa

2013-06-01

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Káarnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

Viewpoints, Formalisms, Languages, and Tools for Cyber-Physical Systems

DTIC Science & Technology

2014-05-16

Organization]: Special-Purpose and Application-Based Systems —real-time and embedded sys- tems; F.1.2 [Computation by Abstract Devices]: Mod- els of...domain CPS is not new. For example, early automotive embedded systems in the 1970s already combined closed-loop control of the brake and engine subsystems...Consider for example the development of an embedded control system such as an advanced driver assistance system (ADAS) (e.g., adaptive cruise control

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

PubMed

Luo, Shaohua; Wu, Songli; Gao, Ruizhen

2015-07-01

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

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

Luo, Shaohua; Department of Mechanical Engineering, Chongqing Aerospace Polytechnic, Chongqing, 400021; Wu, Songli

2015-07-15

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in themore » closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.« less

Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems.

PubMed

Zhao, Xudong; Shi, Peng; Zheng, Xiaolong

2016-06-01

In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Virtual grasping: closed-loop force control using electrotactile feedback.

PubMed

Jorgovanovic, Nikola; Dosen, Strahinja; Djozic, Damir J; Krajoski, Goran; Farina, Dario

2014-01-01

Closing the control loop by providing somatosensory feedback to the user of a prosthesis is a well-known, long standing challenge in the field of prosthetics. Various approaches have been investigated for feedback restoration, ranging from direct neural stimulation to noninvasive sensory substitution methods. Although there are many studies presenting closed-loop systems, only a few of them objectively evaluated the closed-loop performance, mostly using vibrotactile stimulation. Importantly, the conclusions about the utility of the feedback were partly contradictory. The goal of the current study was to systematically investigate the capability of human subjects to control grasping force in closed loop using electrotactile feedback. We have developed a realistic experimental setup for virtual grasping, which operated in real time, included a set of real life objects, as well as a graphical and dynamical model of the prosthesis. We have used the setup to test 10 healthy, able bodied subjects to investigate the role of training, feedback and feedforward control, robustness of the closed loop, and the ability of the human subjects to generalize the control to previously "unseen" objects. Overall, the outcomes of this study are very optimistic with regard to the benefits of feedback and reveal various, practically relevant, aspects of closed-loop control.

Holographic Adaptive Laser Optics System

NASA Astrophysics Data System (ADS)

Andersen, G.; Ghebremichael, F.

2011-09-01

We have created a new adaptive optics system using a holographic modal wavefront sensing method with the autonomous (computer-free) closed-loop control of a MEMS deformable mirror (DM). A multiplexed hologram is recorded using the maximum and minimum actuator positions on the deformable mirror as the “modes”. On reconstruction, an input beam is diffracted into pairs of focal spots and the ratio of the intensities of certain pairs determines the absolute wavefront phase at a particular actuator location. The wavefront measurement is made using fast, sensitive silicon photomultiplier arrays with the parallel outputs directly controlling individual actuators in the MEMS DM. In this talk, we will present the results from an all-optical, ultra-compact system that runs in closed-loop without the need for a computer. The speed is limited only by the response time of any given DM actuator and not the number of actuators. In our case, our 32-actuator prototype device already operates at 10 kHz and our next generation system is being designed for > 100 kHz. As a modal system, it is largely insensitive to scintillation and obscuration and is thus ideal for extreme adaptive optics applications. We will present information on how HALOS can be used for image correction and beam propagation as well as several other novel applications.

A dual-loop model of the human controller in single-axis tracking tasks

NASA Technical Reports Server (NTRS)

Hess, R. A.

1977-01-01

A dual loop model of the human controller in single axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure which involves feeding back that portion of the controlled element output rate which is due to control activity. The sensory inputs to the human controller are assumed to be system error and control force. The former is assumed to be sensed via visual, aural, or tactile displays while the latter is assumed to be sensed in kinesthetic fashion. A nonlinear form of the model is briefly discussed. This model is then linearized and parameterized. A set of general adaptive characteristics for the parameterized model is hypothesized. These characteristics describe the manner in which the parameters in the linearized model will vary with such things as display quality. It is demonstrated that the parameterized model can produce controller describing functions which closely approximate those measured in laboratory tracking tasks for a wide variety of controlled elements.

An evaluation of some strategies for vibration control of flexible rotors

NASA Technical Reports Server (NTRS)

Burrows, C. R.

1992-01-01

There is evidence that the reliability of magnetic bearings has achieved an acceptable level in applications when high cost can be tolerated. This acceptability would be enhanced if the inherent capability of magnetic bearings as active control elements were fully used. The technological and commercial promise of magnetic bearings will be fulfilled only if attention is focussed on the control problems associated with their use. The open loop adaptive control algorithm provides an efficient method of controlling the vibration of rotors without the need of a prior knowledge of parameter values. It overcomes the disadvantages normally associated with open loop control while avoiding the problem of instability associated with closed loop control algorithms. The algorithm is conceptually satisfying because it uses the capability of magnetic bearings as fully active vibration control elements rather than limiting them to act as adjustable stiffness and damping elements, as is the case when they are used with local position and velocity feedback.

Active telescope systems; Proceedings of the Meeting, Orlando, FL, Mar. 28-31, 1989

NASA Astrophysics Data System (ADS)

Roddier, Francois J.

1989-09-01

The present conference discusses topics in the fundamental limitations of adaptive optics in astronomical telescopy, integrated telescope systems designs, novel components for adaptive telescopes, active interferometry, flexible-mirror and segmented-mirror telescopes, and various aspects of the NASA Precision Segmented Reflectors Program. Attention is given to near-ground atmospheric turbulence effects, a near-IR astronomical adaptive optics system, a simplified wavefront sensor for adaptive mirror control, excimer laser guide star techniques for adaptive astronomical imaging, active systems in long-baseline interferometry, mirror figure control primitives for a 10-m primary mirror, and closed-loop active optics for large flexible mirrors subject to wind buffet deformations. Also discussed are active pupil geometry control for a phased-array telescope, extremely lightweight space telescope mirrors, segmented-mirror manufacturing tolerances, and composite deformable mirror design.

Adaptive optics for peripheral vision

NASA Astrophysics Data System (ADS)

Rosén, R.; Lundström, L.; Unsbo, P.

2012-07-01

Understanding peripheral optical errors and their impact on vision is important for various applications, e.g. research on myopia development and optical correction of patients with central visual field loss. In this study, we investigated whether correction of higher order aberrations with adaptive optics (AO) improve resolution beyond what is achieved with best peripheral refractive correction. A laboratory AO system was constructed for correcting peripheral aberrations. The peripheral low contrast grating resolution acuity in the 20° nasal visual field of the right eye was evaluated for 12 subjects using three types of correction: refractive correction of sphere and cylinder, static closed loop AO correction and continuous closed loop AO correction. Running AO in continuous closed loop improved acuity compared to refractive correction for most subjects (maximum benefit 0.15 logMAR). The visual improvement from aberration correction was highly correlated with the subject's initial amount of higher order aberrations (p = 0.001, R 2 = 0.72). There was, however, no acuity improvement from static AO correction. In conclusion, correction of peripheral higher order aberrations can improve low contrast resolution, provided refractive errors are corrected and the system runs in continuous closed loop.

Wavefront sensorless adaptive optics versus sensor-based adaptive optics for in vivo fluorescence retinal imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wahl, Daniel J.; Zhang, Pengfei; Jian, Yifan; Bonora, Stefano; Sarunic, Marinko V.; Zawadzki, Robert J.

2017-02-01

Adaptive optics (AO) is essential for achieving diffraction limited resolution in large numerical aperture (NA) in-vivo retinal imaging in small animals. Cellular-resolution in-vivo imaging of fluorescently labeled cells is highly desirable for studying pathophysiology in animal models of retina diseases in pre-clinical vision research. Currently, wavefront sensor-based (WFS-based) AO is widely used for retinal imaging and has demonstrated great success. However, the performance can be limited by several factors including common path errors, wavefront reconstruction errors and an ill-defined reference plane on the retina. Wavefront sensorless (WFS-less) AO has the advantage of avoiding these issues at the cost of algorithmic execution time. We have investigated WFS-less AO on a fluorescence scanning laser ophthalmoscopy (fSLO) system that was originally designed for WFS-based AO. The WFS-based AO uses a Shack-Hartmann WFS and a continuous surface deformable mirror in a closed-loop control system to measure and correct for aberrations induced by the mouse eye. The WFS-less AO performs an open-loop modal optimization with an image quality metric. After WFS-less AO aberration correction, the WFS was used as a control of the closed-loop WFS-less AO operation. We can easily switch between WFS-based and WFS-less control of the deformable mirror multiple times within an imaging session for the same mouse. This allows for a direct comparison between these two types of AO correction for fSLO. Our results demonstrate volumetric AO-fSLO imaging of mouse retinal cells labeled with GFP. Most significantly, we have analyzed and compared the aberration correction results for WFS-based and WFS-less AO imaging.

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

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

PubMed

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

2016-11-01

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

Variable Neural Adaptive Robust Control: A Switched System Approach

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

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 piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less

Step-control of electromechanical systems

DOEpatents

Lewis, Robert N.

1979-01-01

The response of an automatic control system to a general input signal is improved by applying a test input signal, observing the response to the test input signal and determining correctional constants necessary to provide a modified input signal to be added to the input to the system. A method is disclosed for determining correctional constants. The modified input signal, when applied in conjunction with an operating signal, provides a total system output exhibiting an improved response. This method is applicable to open-loop or closed-loop control systems. The method is also applicable to unstable systems, thus allowing controlled shut-down before dangerous or destructive response is achieved and to systems whose characteristics vary with time, thus resulting in improved adaptive systems.

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

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

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

Adaptive robust fault tolerant control design for a class of nonlinear uncertain MIMO systems with quantization.

PubMed

Ao, Wei; Song, Yongdong; Wen, Changyun

2017-05-01

In this paper, we investigate the adaptive control problem for a class of nonlinear uncertain MIMO systems with actuator faults and quantization effects. Under some mild conditions, an adaptive robust fault-tolerant control is developed to compensate the affects of uncertainties, actuator failures and errors caused by quantization, and a range of the parameters for these quantizers is established. Furthermore, a Lyapunov-like approach is adopted to demonstrate that the ultimately uniformly bounded output tracking error is guaranteed by the controller, and the signals of the closed-loop system are ensured to be bounded, even in the presence of at most m-q actuators stuck or outage. Finally, numerical simulations are provided to verify and illustrate the effectiveness of the proposed adaptive schemes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

AOF LTAO mode: reconstruction strategy and first test results

NASA Astrophysics Data System (ADS)

Oberti, Sylvain; Kolb, Johann; Le Louarn, Miska; La Penna, Paolo; Madec, Pierre-Yves; Neichel, Benoit; Sauvage, Jean-François; Fusco, Thierry; Donaldson, Robert; Soenke, Christian; Suárez Valles, Marcos; Arsenault, Robin

2016-07-01

GALACSI is the Adaptive Optics (AO) system serving the instrument MUSE in the framework of the Adaptive Optics Facility (AOF) project. Its Narrow Field Mode (NFM) is a Laser Tomography AO (LTAO) mode delivering high resolution in the visible across a small Field of View (FoV) of 7.5" diameter around the optical axis. From a reconstruction standpoint, GALACSI NFM intends to optimize the correction on axis by estimating the turbulence in volume via a tomographic process, then projecting the turbulence profile onto one single Deformable Mirror (DM) located in the pupil, close to the ground. In this paper, the laser tomographic reconstruction process is described. Several methods (virtual DM, virtual layer projection) are studied, under the constraint of a single matrix vector multiplication. The pseudo-synthetic interaction matrix model and the LTAO reconstructor design are analysed. Moreover, the reconstruction parameter space is explored, in particular the regularization terms. Furthermore, we present here the strategy to define the modal control basis and split the reconstruction between the Low Order (LO) loop and the High Order (HO) loop. Finally, closed loop performance obtained with a 3D turbulence generator will be analysed with respect to the most relevant system parameters to be tuned.

Review article: closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization?

PubMed

Rinehart, Joseph; Liu, Ngai; Alexander, Brenton; Cannesson, Maxime

2012-01-01

Closed-loop (automated) controllers are encountered in all aspects of modern life in applications ranging from air-conditioning to spaceflight. Although these systems are virtually ubiquitous, they are infrequently used in anesthesiology because of the complexity of physiologic systems and the difficulty in obtaining reliable and valid feedback data from the patient. Despite these challenges, closed-loop systems are being increasingly studied and improved for medical use. Two recent developments have made fluid administration a candidate for closed-loop control. First, the further description and development of dynamic predictors of fluid responsiveness provides a strong parameter for use as a control variable to guide fluid administration. Second, rapid advances in noninvasive monitoring of cardiac output and other hemodynamic variables make goal-directed therapy applicable for a wide range of patients in a variety of clinical care settings. In this article, we review the history of closed-loop controllers in clinical care, discuss the current understanding and limitations of the dynamic predictors of fluid responsiveness, and examine how these variables might be incorporated into a closed-loop fluid administration system.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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.

Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer.

PubMed

He, Wei; Yan, Zichen; Sun, Changyin; Chen, Yunan

2017-10-01

The research of this paper works out the attitude and position control of the flapping wing micro aerial vehicle (FWMAV). Neural network control with full state and output feedback are designed to deal with uncertainties in this complex nonlinear FWMAV dynamic system and enhance the system robustness. Meanwhile, we design disturbance observers which are exerted into the FWMAV system via feedforward loops to counteract the bad influence of disturbances. Then, a Lyapunov function is proposed to prove the closed-loop system stability and the semi-global uniform ultimate boundedness of all state variables. Finally, a series of simulation results indicate that proposed controllers can track desired trajectories well via selecting appropriate control gains. And the designed controllers possess potential applications in FWMAVs.

In-Flight Suppression of an Unstable F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Gilligan, Eric T.; Wall, John H.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off-nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using post-flight frequency-domain reconstruction, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

PubMed

Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

2016-12-08

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

PubMed

Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

2017-01-01

Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Lin, Chong; Liu, Xiaoping; Liu, Kefu

2015-12-01

This paper focuses on the problem of fuzzy adaptive control for a class of multiinput and multioutput (MIMO) nonlinear systems in nonstrict-feedback form, which contains the strict-feedback form as a special case. By the condition of variable partition, a new fuzzy adaptive backstepping is proposed for such a class of nonlinear MIMO systems. The suggested fuzzy adaptive controller guarantees that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors eventually converge to a small neighborhood around the origin. The main advantage of this paper is that a control approach is systematically derived for nonlinear systems with strong interconnected terms which are the functions of all states of the whole system. Simulation results further illustrate the effectiveness of the suggested approach.

Latest developments on the loop control system of AdOpt@TNG

NASA Astrophysics Data System (ADS)

Ghedina, Adriano; Gaessler, Wolfgang; Cecconi, Massimo; Ragazzoni, Roberto; Puglisi, Alfio T.; De Bonis, Fulvio

2004-10-01

The Adaptive Optics System of the Galileo Telescope (AdOpt@TNG) is the only adaptive optics system mounted on a telescope which uses a pyramid wavefront snesor and it has already shown on sky its potentiality. Recently AdOpt@TNG has undergone deep changes at the level of its higher orders control system. The CCD and the Real Time Computer (RTC) have been substituted as a whole. Instead of the VME based RTC, due to its frequent breakdowns, a dual pentium processor PC with Real-Time-Linux has been chosen. The WFS CCD, that feeds the images to the RTC, was changed to an off-the-shelf camera system from SciMeasure with an EEV39 80x80 pixels as detector. While the APD based Tip/Tilt loop has shown the quality on the sky at the TNG site and the ability of TNG to take advantage of this quality, up to the diffraction limit, the High-Order system has been fully re-developed and the performance of the closed loop is under evaluation to offer the system with the best performance to the astronomical community.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

On-line pulse control for structural and mechanical systems

NASA Technical Reports Server (NTRS)

Udwadia, F. E.; Garba, J. A.; Tabaie, S.

1981-01-01

This paper studies the feasibility of using open-loop adaptive on-line pulse control for limiting the response of large linear multidegree of freedom systems subjected to general dynamic loading environments. Pulses of short durations are used to control the system when the system response exceeds a given threshold level. The pulse magnitudes are obtained in closed form, leading to large computational efficiencies when compared with optimal control theoretic methods. The technique is illustrated for a structural system subjected to earthquake-like base excitations.

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.

Instrument control software development process for the multi-star AO system ARGOS

NASA Astrophysics Data System (ADS)

Kulas, M.; Barl, L.; Borelli, J. L.; Gässler, W.; Rabien, S.

2012-09-01

The ARGOS project (Advanced Rayleigh guided Ground layer adaptive Optics System) will upgrade the Large Binocular Telescope (LBT) with an AO System consisting of six Rayleigh laser guide stars. This adaptive optics system integrates several control loops and many different components like lasers, calibration swing arms and slope computers that are dispersed throughout the telescope. The purpose of the instrument control software (ICS) is running this AO system and providing convenient client interfaces to the instruments and the control loops. The challenges for the ARGOS ICS are the development of a distributed and safety-critical software system with no defects in a short time, the creation of huge and complex software programs with a maintainable code base, the delivery of software components with the desired functionality and the support of geographically distributed project partners. To tackle these difficult tasks, the ARGOS software engineers reuse existing software like the novel middleware from LINC-NIRVANA, an instrument for the LBT, provide many tests at different functional levels like unit tests and regression tests, agree about code and architecture style and deliver software incrementally while closely collaborating with the project partners. Many ARGOS ICS components are already successfully in use in the laboratories for testing ARGOS control loops.

Neural-Network-Based Adaptive Decentralized Fault-Tolerant Control for a Class of Interconnected Nonlinear Systems.

PubMed

Li, Xiao-Jian; Yang, Guang-Hong

2018-01-01

This paper is concerned with the adaptive decentralized fault-tolerant tracking control problem for a class of uncertain interconnected nonlinear systems with unknown strong interconnections. An algebraic graph theory result is introduced to address the considered interconnections. In addition, to achieve the desirable tracking performance, a neural-network-based robust adaptive decentralized fault-tolerant control (FTC) scheme is given to compensate the actuator faults and system uncertainties. Furthermore, via the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are semiglobally bounded, and the tracking errors of each subsystem exponentially converge to a compact set, whose radius is adjustable by choosing different controller design parameters. Finally, the effectiveness and advantages of the proposed FTC approach are illustrated with two simulated examples.

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.

Adaptive Fuzzy Output Constrained Control Design for Multi-Input Multioutput Stochastic Nonstrict-Feedback Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-12-01

In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Timing characterization and analysis of the Linux-based, closed loop control computer for the Subaru Telescope laser guide star adaptive optics system

NASA Astrophysics Data System (ADS)

Dinkins, Matthew; Colley, Stephen

2008-07-01

Hardware and software specialized for real time control reduce the timing jitter of executables when compared to off-the-shelf hardware and software. However, these specialized environments are costly in both money and development time. While conventional systems have a cost advantage, the jitter in these systems is much larger and potentially problematic. This study analyzes the timing characterstics of a standard Dell server running a fully featured Linux operating system to determine if such a system would be capable of meeting the timing requirements for closed loop operations. Investigations are preformed on the effectiveness of tools designed to make off-the-shelf system performance closer to specialized real time systems. The Gnu Compiler Collection (gcc) is compared to the Intel C Compiler (icc), compiler optimizations are investigated, and real-time extensions to Linux are evaluated.

Double closed-loop cascade control for lower limb exoskeleton with elastic actuation.

PubMed

Zhu, Yanhe; Zheng, Tianjiao; Jin, Hongzhe; Yang, Jixing; Zhao, Jie

2015-01-01

Unlike traditional rigid actuators, the significant features of Series Elastic Actuator (SEA) are stable torque control, lower output impedance, impact resistance and energy storage. Recently, SEA has been applied in many exoskeletons. In such applications, a key issue is how to realize the human-exoskeleton movement coordination. In this paper, double closed-loop cascade control for lower limb exoskeleton with SEA is proposed. This control method consists of inner SEA torque loop and outer contact force loop. Utilizing the SEA torque control with a motor velocity loop, actuation performances of SEA are analyzed. An integrated exoskeleton control system is designed, in which joint angles are calculated by internal encoders and resolvers and contact forces are gathered by external pressure sensors. The double closed-loop cascade control model is established based on the feedback signals of internal and external sensor. Movement experiments are accomplished in our prototype of lower limb exoskeleton. Preliminary results indicate the exoskeleton movements with pilot can be realized stably by utilizing this double closed-loop cascade control method. Feasibility of the SEA in our exoskeleton robot and effectiveness of the control method are verified.

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

PubMed

Nwagoum Tuwa, Peguy Roussel; Woafo, P

2018-01-01

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

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

Differential flatness properties and multivariable adaptive control of ovarian system dynamics

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos

2016-12-01

The ovarian system exhibits nonlinear dynamics which is modeled by a set of coupled nonlinear differential equations. The paper proposes adaptive fuzzy control based on differential flatness theory for the complex dynamics of the ovarian system. It is proven that the dynamic model of the ovarian system, having as state variables the LH and the FSH hormones and their derivatives, is a differentially flat one. This means that all its state variables and its control inputs can be described as differential functions of the flat output. By exploiting differential flatness properties the system's dynamic model is written in the multivariable linear canonical (Brunovsky) form, for which the design of a state feedback controller becomes possible. After this transformation, the new control inputs of the system contain unknown nonlinear parts, which are identified with the use of neurofuzzy approximators. The learning procedure for these estimators is determined by the requirement the first derivative of the closed-loop's Lyapunov function to be a negative one. Moreover, Lyapunov stability analysis shows that H-infinity tracking performance is succeeded for the feedback control loop and this assures improved robustness to the aforementioned model uncertainty as well as to external perturbations. The efficiency of the proposed adaptive fuzzy control scheme is confirmed through simulation experiments.

Closed-loop analysis and control of a non-inverting buck-boost converter

NASA Astrophysics Data System (ADS)

Chen, Zengshi; Hu, Jiangang; Gao, Wenzhong

2010-11-01

In this article, a cascade controller is designed and analysed for a non-inverting buck-boost converter. The fast inner current loop uses sliding mode control. The slow outer voltage loop uses the proportional-integral (PI) control. Stability analysis and selection of PI gains are based on the nonlinear closed-loop error dynamics incorporating both the inner and outer loop controllers. The closed-loop system is proven to have a nonminimum phase structure. The voltage transient due to step changes of input voltage or resistance is predictable. The operating range of the reference voltage is discussed. The controller is validated by a simulation circuit. The simulation results show that the reference output voltage is well-tracked under system uncertainties or disturbances, confirming the validity of the proposed controller.

Shape Morphing Adaptive Radiator Technology (SMART) Updates to Techport Entry

NASA Technical Reports Server (NTRS)

Erickson, Lisa; Bertagne, Christopher; Hartl, Darren; Witcomb, John; Cognata, Thomas

2017-01-01

The Shape-Morphing Adaptive Radiator Technology (SMART) project builds off the FY16 research effort that developed a flexible composite radiator panel and demonstrated its ability to actuate from SMA's attached to it. The proposed FY17 Shape-Morphing Adaptive Radiator Technology (SMART) project's goal is to 1) develop a practical radiator design with shape memory alloys (SMAs) bonded to the radiator's panel, and 2) build a multi-panel radiator prototype for subsequent system level thermal vacuum tests. The morphing radiator employs SMA materials to passively change its shape to adapt its rate of heat rejection to vehicle requirements. Conceptually, the radiator panel has a naturally closed position (like a cylinder) in a cold environment. Whenever the radiator's temperature gradually rises, SMA's affixed to the face sheet will pull the face sheet open a commensurate amount - increasing the radiators view to space and causing it to reject more heat. In a vehicle, the radiator's variable heat rejection capabilities would reduce the number of additional heat rejection devices in a vehicle's thermal control system. This technology aims to help achieve the required maximum to minimum heat rejection ratio required for manned space vehicles to adopt a lighter, simpler, single loop thermal control architecture (ATCS). Single loop architectures are viewed as an attractive means to reduce mass and complexity over traditional dual-loop solutions. However, fluids generally considered safe enough to flow within crewed cabins (e.g. propylene glycol-water mixtures) have much higher freezing points and viscosities than those used in the external sides of dual loop ATCSs (e.g. Ammonia and HFE7000).

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

A Triple-Loop Inductive Power Transmission System for Biomedical Applications.

PubMed

Lee, Byunghun; Kiani, Mehdi; Ghovanloo, Maysam

2016-02-01

A triple-loop wireless power transmission (WPT) system equipped with closed-loop global power control, adaptive transmitter (Tx) resonance compensation (TRC), and automatic receiver (Rx) resonance tuning (ART) is presented. This system not only opposes coupling and load variations but also compensates for changes in the environment surrounding the inductive link to enhance power transfer efficiency (PTE) in applications such as implantable medical devices (IMDs). The Tx was built around a commercial off-the-shelf (COTS) radio-frequency identification (RFID) reader, operating at 13.56 MHz. A local Tx loop finds the optimal capacitance in parallel with the Tx coil by adjusting a varactor. A global power control loop maintains the received power at a desired level in the presence of changes in coupling distance, coil misalignments, and loading. Moreover, a local Rx loop is implemented inside a power management integrated circuit (PMIC) to avoid PTE degradation due to the Rx coil surrounding environment and process variations. The PMIC was fabricated in a 0.35- μm 4M2P standard CMOS process with 2.54 mm(2) active area. Measurement results show that the proposed triple-loop system improves the overall PTE by up to 10.5% and 4.7% compared to a similar open- and single closed-loop system, respectively, at nominal coil distance of 2 cm. The added TRC and ART loops contribute 2.3% and 1.4% to the overall PTE of 13.5%, respectively. This is the first WPT system to include three loops to dynamically compensate for environment and circuit variations and improve the overall power efficiency all the way from the driver output in Tx to the load in Rx.

PID Tuning Using Extremum Seeking

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

Killingsworth, N; Krstic, M

2005-11-15

Although proportional-integral-derivative (PID) controllers are widely used in the process industry, their effectiveness is often limited due to poor tuning. Manual tuning of PID controllers, which requires optimization of three parameters, is a time-consuming task. To remedy this difficulty, much effort has been invested in developing systematic tuning methods. Many of these methods rely on knowledge of the plant model or require special experiments to identify a suitable plant model. Reviews of these methods are given in [1] and the survey paper [2]. However, in many situations a plant model is not known, and it is not desirable to openmore » the process loop for system identification. Thus a method for tuning PID parameters within a closed-loop setting is advantageous. In relay feedback tuning [3]-[5], the feedback controller is temporarily replaced by a relay. Relay feedback causes most systems to oscillate, thus determining one point on the Nyquist diagram. Based on the location of this point, PID parameters can be chosen to give the closed-loop system a desired phase and gain margin. An alternative tuning method, which does not require either a modification of the system or a system model, is unfalsified control [6], [7]. This method uses input-output data to determine whether a set of PID parameters meets performance specifications. An adaptive algorithm is used to update the PID controller based on whether or not the controller falsifies a given criterion. The method requires a finite set of candidate PID controllers that must be initially specified [6]. Unfalsified control for an infinite set of PID controllers has been developed in [7]; this approach requires a carefully chosen input signal [8]. Yet another model-free PID tuning method that does not require opening of the loop is iterative feedback tuning (IFT). IFT iteratively optimizes the controller parameters with respect to a cost function derived from the output signal of the closed-loop system, see [9]. This method is based on the performance of the closed-loop system during a step response experiment [10], [11]. In this article we present a method for optimizing the step response of a closed-loop system consisting of a PID controller and an unknown plant with a discrete version of extremum seeking (ES). Specifically, ES is used to minimize a cost function similar to that used in [10], [11], which quantifies the performance of the PID controller. ES, a non-model-based method, iteratively modifies the arguments (in this application the PID parameters) of a cost function so that the output of the cost function reaches a local minimum or local maximum. In the next section we apply ES to PID controller tuning. We illustrate this technique through simulations comparing the effectiveness of ES to other PID tuning methods. Next, we address the importance of the choice of cost function and consider the effect of controller saturation. Furthermore, we discuss the choice of ES tuning parameters. Finally, we offer some conclusions.« less

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

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

PubMed

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

2011-07-01

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

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

PubMed

Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

2014-09-01

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.

An adaptive trajectory tracking control of four rotor hover vehicle using extended normalized radial basis function network

NASA Astrophysics Data System (ADS)

ul Amin, Rooh; Aijun, Li; Khan, Muhammad Umer; Shamshirband, Shahaboddin; Kamsin, Amirrudin

2017-01-01

In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.

Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

PubMed

Tong, Shaocheng; Li, Yongming

2017-02-01

This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs.

PubMed

Shi, Wuxi; Luo, Rui; Li, Baoquan

2017-01-01

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A unified perspective on robot control - The energy Lyapunov function approach

NASA Technical Reports Server (NTRS)

Wen, John T.

1990-01-01

A unified framework for the stability analysis of robot tracking control is presented. By using an energy-motivated Lyapunov function candidate, the closed-loop stability is shown for a large family of control laws sharing a common structure of proportional and derivative feedback and a model-based feedforward. The feedforward can be zero, partial or complete linearized dynamics, partial or complete nonlinear dynamics, or linearized or nonlinear dynamics with parameter adaptation. As result, the dichotomous approaches to the robot control problem based on the open-loop linearization and nonlinear Lyapunov analysis are both included in this treatment. Furthermore, quantitative estimates of the trade-offs between different schemes in terms of the tracking performance, steady state error, domain of convergence, realtime computation load and required a prior model information are derived.

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

PubMed

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

2017-10-01

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

The role of experience in flight behaviour of Drosophila.

PubMed

Hesselberg, Thomas; Lehmann, Fritz-Olaf

2009-10-01

Experience plays a key role in the acquisition of complex motor skills in running and flight of many vertebrates. To evaluate the significance of previous experience for the efficiency of motor behaviour in an insect, we investigated the flight behaviour of the fruit fly Drosophila. We reared flies in chambers in which the animals could freely walk and extend their wings, but could not gain any flight experience. These naive animals were compared with control flies under both open- and closed-loop tethered flight conditions in a flight simulator as well as in a free-flight arena. The data suggest that the overall flight behaviour in Drosophila seems to be predetermined because both groups exhibited similar mean stroke amplitude and stroke frequency, similar open-loop responses to visual stimulation and the immediate ability to track visual objects under closed-loop feedback conditions. In short free flight bouts, peak saccadic turning rate, angular acceleration, peak horizontal speed and flight altitude were also similar in naive and control flies. However, we found significant changes in other key parameters in naive animals such as a reduction in mean horizontal speed (-23%) and subtle changes in mean turning rate (-48%). Naive flies produced 25% less yaw torque-equivalent stroke amplitudes than the controls in response to a visual stripe rotating in open loop around the tethered animal, potentially suggesting a flight-dependent adaptation of the visuo-motor gain in the control group. This change ceased after the animals experienced visual closed-loop feedback. During closed-loop flight conditions, naive flies had 53% larger differences in left and right stroke amplitude when fixating a visual object, thus steering control was less precise. We discuss two alternative hypotheses to explain our results: the ;neuronal experience' hypothesis, suggesting that there are some elements of learning and fine-tuning involved during the first flight experiences in Drosophila and the ;muscular exercise' hypothesis. Our experiments support the first hypothesis because maximum locomotor capacity seems not to be significantly impaired in the naive group. Although this study primarily confirms the genetic pre-disposition for flight in Drosophila, previous experience may apparently adjust locomotor fine control and aerial performance, although this effect seems to be small compared with vertebrates.

A control system design approach for flexible spacecraft

NASA Technical Reports Server (NTRS)

Silverberg, L. M.

1985-01-01

A control system design approach for flexible spacecraft is presented. The control system design is carried out in two steps. The first step consists of determining the ideal control system in terms of a desirable dynamic performance. The second step consists of designing a control system using a limited number of actuators that possess a dynamic performance that is close to the ideal dynamic performance. The effects of using a limited number of actuators is that the actual closed-loop eigenvalues differ from the ideal closed-loop eigenvalues. A method is presented to approximate the actual closed-loop eigenvalues so that the calculation of the actual closed-loop eigenvalues can be avoided. Depending on the application, it also may be desirable to apply the control forces as impulses. The effect of digitizing the control to produce the appropriate impulses is also examined.

Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.

PubMed

Wang, Wei; Tong, Shaocheng

2018-02-01

This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.

Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.

In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

Wave field synthesis, adaptive wave field synthesis and ambisonics using decentralized transformed control: Potential applications to sound field reproduction and active noise control

NASA Astrophysics Data System (ADS)

Gauthier, Philippe-Aubert; Berry, Alain; Woszczyk, Wieslaw

2005-09-01

Sound field reproduction finds applications in listening to prerecorded music or in synthesizing virtual acoustics. The objective is to recreate a sound field in a listening environment. Wave field synthesis (WFS) is a known open-loop technology which assumes that the reproduction environment is anechoic. Classical WFS, therefore, does not perform well in a real reproduction space such as room. Previous work has suggested that it is physically possible to reproduce a progressive wave field in-room situation using active control approaches. In this paper, a formulation of adaptive wave field synthesis (AWFS) introduces practical possibilities for an adaptive sound field reproduction combining WFS and active control (with WFS departure penalization) with a limited number of error sensors. AWFS includes WFS and closed-loop ``Ambisonics'' as limiting cases. This leads to the modification of the multichannel filtered-reference least-mean-square (FXLMS) and the filtered-error LMS (FELMS) adaptive algorithms for AWFS. Decentralization of AWFS for sound field reproduction is introduced on the basis of sources' and sensors' radiation modes. Such decoupling may lead to decentralized control of source strength distributions and may reduce computational burden of the FXLMS and the FELMS algorithms used for AWFS. [Work funded by NSERC, NATEQ, Université de Sherbrooke and VRQ.] Ultrasound/Bioresponse to

Semi-active control of helicopter vibration using controllable stiffness and damping devices

NASA Astrophysics Data System (ADS)

Anusonti-Inthra, Phuriwat

Semi-active concepts for helicopter vibration reduction are developed and evaluated in this dissertation. Semi-active devices, controllable stiffness devices or controllable orifice dampers, are introduced; (i) in the blade root region (rotor-based concept) and (ii) between the rotor and the fuselage as semi-active isolators (in the non-rotating frame). Corresponding semi-active controllers for helicopter vibration reduction are also developed. The effectiveness of the rotor-based semi-active vibration reduction concept (using stiffness and damping variation) is demonstrated for a 4-bladed hingeless rotor helicopter in moderate- to high-speed forward flight. A sensitivity study shows that the stiffness variation of root element can reduce hub vibrations when proper amplitude and phase are used. Furthermore, the optimal semi-active control scheme can determine the combination of stiffness variations that produce significant vibration reduction in all components of vibratory hub loads simultaneously. It is demonstrated that desired cyclic variations in properties of the blade root region can be practically achieved using discrete controllable stiffness devices and controllable dampers, especially in the flap and lag directions. These discrete controllable devices can produce 35--50% reduction in a composite vibration index representing all components of vibratory hub loads. No detrimental increases are observed in the lower harmonics of blade loads and blade response (which contribute to the dynamic stresses) and controllable device internal loads, when the optimal stiffness and damping variations are introduced. The effectiveness of optimal stiffness and damping variations in reducing hub vibration is retained over a range of cruise speeds and for variations in fundamental rotor properties. The effectiveness of the semi-active isolator is demonstrated for a simplified single degree of freedom system representing the semi-active isolation system. The rotor, represented by a lumped mass under harmonic force excitation, is supported by a spring and a parallel damper on the fuselage (assumed to have infinite mass). Properties of the spring or damper can then be controlled to reduce transmission of the force into the fuselage or the support structure. This semi-active isolation concept can produce additional 30% vibration reduction beyond the level achieved by a passive isolator. Different control schemes (i.e. open-loop, closed-loop, and closed-loop adaptive schemes) are developed and evaluated to control transmission of vibratory loads to the support structure (fuselage), and it is seen that a closed-loop adaptive controller is required to retain vibration reduction effectiveness when there is a change in operating condition. (Abstract shortened by UMI.)

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

Luo, Shaohua; School of Automation, Chongqing University, Chongqing 400044; Sun, Quanping

This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Puttingmore » tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.« less

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.

Pre-frontal control of closed-loop limbic neurostimulation by rodents using a brain-computer interface

NASA Astrophysics Data System (ADS)

Widge, Alik S.; Moritz, Chet T.

2014-04-01

Objective. There is great interest in closed-loop neurostimulators that sense and respond to a patient's brain state. Such systems may have value for neurological and psychiatric illnesses where symptoms have high intraday variability. Animal models of closed-loop stimulators would aid preclinical testing. We therefore sought to demonstrate that rodents can directly control a closed-loop limbic neurostimulator via a brain-computer interface (BCI). Approach. We trained rats to use an auditory BCI controlled by single units in prefrontal cortex (PFC). The BCI controlled electrical stimulation in the medial forebrain bundle, a limbic structure involved in reward-seeking. Rigorous offline analyses were performed to confirm volitional control of the neurostimulator. Main results. All animals successfully learned to use the BCI and neurostimulator, with closed-loop control of this challenging task demonstrated at 80% of PFC recording locations. Analysis across sessions and animals confirmed statistically robust BCI control and specific, rapid modulation of PFC activity. Significance. Our results provide a preliminary demonstration of a method for emotion-regulating closed-loop neurostimulation. They further suggest that activity in PFC can be used to control a BCI without pre-training on a predicate task. This offers the potential for BCI-based treatments in refractory neurological and mental illness.

Neuromimetic Event-Based Detection for Closed-Loop Tactile Feedback Control of Upper Limb Prostheses

PubMed Central

Osborn, Luke; Kaliki, Rahul; Soares, Alcimar; Thakor, Nitish

2016-01-01

Upper limb amputees lack the valuable tactile sensing that helps provide context about the surrounding environment. Here we utilize tactile information to provide active touch feedback to a prosthetic hand. First, we developed fingertip tactile sensors for producing biomimetic spiking responses for monitoring contact, release, and slip of an object grasped by a prosthetic hand. We convert the sensor output into pulses, mimicking the rapid and slowly adapting spiking responses of receptor afferents found in the human body. Second, we designed and implemented two neuromimetic event-based algorithms, Compliant Grasping and Slip Prevention, on a prosthesis to create a local closed-loop tactile feedback control system (i.e. tactile information is sent to the prosthesis). Grasping experiments were designed to assess the benefit of this biologically inspired neuromimetic tactile feedback to a prosthesis. Results from able-bodied and amputee subjects show the average number of objects that broke or slipped during grasping decreased by over 50% and the average time to complete a grasping task decreased by at least 10% for most trials when comparing neuromimetic tactile feedback with no feedback on a prosthesis. Our neuromimetic method of closed-loop tactile sensing is a novel approach to improving the function of upper limb prostheses. PMID:27777640

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain

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

Luo, Shaohua

This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaosmore » of PMSM and show the effectiveness and robustness of the proposed method.« less

Adaptive fuzzy dynamic surface control for the chaotic permanent magnet synchronous motor using Nussbaum gain.

PubMed

Luo, Shaohua

2014-09-01

This paper is concerned with the problem of adaptive fuzzy dynamic surface control (DSC) for the permanent magnet synchronous motor (PMSM) system with chaotic behavior, disturbance and unknown control gain and parameters. Nussbaum gain is adopted to cope with the situation that the control gain is unknown. And the unknown items can be estimated by fuzzy logic system. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the system output eventually converges to a small neighborhood of the desired reference signal. Finally, the numerical simulations indicate that the proposed scheme can suppress the chaos of PMSM and show the effectiveness and robustness of the proposed method.

Antenna Linear-Quadratic-Gaussian (LQG) Ccontrollers: Properties, Limits of Performance, and Tuning

NASA Technical Reports Server (NTRS)

Gawronski, Wodek K.

2004-01-01

The LQG controllers significantly improve antenna tracking precision, but their tuning is a trial-and-error process. A control engineer has two tools to tune an LQG controller: the choice of coordinate system of the controller, and the selection of weights of the LQG performance index. The paper selects the coordinates of the open-loop model that simplify the shaping of the closed-loop performance. and analyzes the impact of thc weights on the antenna closed-loop bandwidth, disturbance rejection properties, and antenna acceleration. Finally, it presents the LQG controller tuning procedure that rationally shapes the closed-loop performance.

Sensory feedback in prosthetics: a standardized test bench for closed-loop control.

PubMed

Dosen, Strahinja; Markovic, Marko; Hartmann, Cornelia; Farina, Dario

2015-03-01

Closing the control loop by providing sensory feedback to the user of a prosthesis is an important challenge, with major impact on the future of prosthetics. Developing and comparing closed-loop systems is a difficult task, since there are many different methods and technologies that can be used to implement each component of the system. Here, we present a test bench developed in Matlab Simulink for configuring and testing the closed-loop human control system in standardized settings. The framework comprises a set of connected generic blocks with normalized inputs and outputs, which can be customized by selecting specific implementations from a library of predefined components. The framework is modular and extensible and it can be used to configure, compare and test different closed-loop system prototypes, thereby guiding the development towards an optimal system configuration. The use of the test bench was demonstrated by investigating two important aspects of closed-loop control: performance of different electrotactile feedback interfaces (spatial versus intensity coding) during a pendulum stabilization task and feedforward methods (joystick versus myocontrol) for force control. The first experiment demonstrated that in the case of trained subjects the intensity coding might be superior to spatial coding. In the second experiment, the control of force was rather poor even with a stable and precise control interface (joystick), demonstrating that inherent characteristics of the prosthesis can be an important limiting factor when considering the overall effectiveness of the closed-loop control. The presented test bench is an important instrument for investigating different aspects of human manual control with sensory feedback.

Adaptive fixed-time trajectory tracking control of a stratospheric airship.

PubMed

Zheng, Zewei; Feroskhan, Mir; Sun, Liang

2018-05-01

This paper addresses the fixed-time trajectory tracking control problem of a stratospheric airship. By extending the method of adding a power integrator to a novel adaptive fixed-time control method, the convergence of a stratospheric airship to its reference trajectory is guaranteed to be achieved within a fixed time. The control algorithm is firstly formulated without the consideration of external disturbances to establish the stability of the closed-loop system in fixed-time and demonstrate that the convergence time of the airship is essentially independent of its initial conditions. Subsequently, a smooth adaptive law is incorporated into the proposed fixed-time control framework to provide the system with robustness to external disturbances. Theoretical analyses demonstrate that under the adaptive fixed-time controller, the tracking errors will converge towards a residual set in fixed-time. The results of a comparative simulation study with other recent methods illustrate the remarkable performance and superiority of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-04-01

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

Neural self-tuning adaptive control of non-minimum phase system

NASA Technical Reports Server (NTRS)

Ho, Long T.; Bialasiewicz, Jan T.; Ho, Hai 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.

Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.

PubMed

Huang, Yingbo; Na, Jing; Wu, Xing; Liu, Xiaoqin; Guo, Yu

2015-01-01

This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices

NASA Astrophysics Data System (ADS)

Chen, Xi; Li, Yancheng; Li, Jianchun; Gu, Xiaoyu

2018-01-01

Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov’s direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.

Robust Adaptive Flight Control Design of Air-breathing Hypersonic Vehicles

DTIC Science & Technology

2016-12-07

dynamic inversion controller design for a non -minimum phase hypersonic vehicle is derived by Kuipers et al. [2008]. Moreover, integrated guidance and...stabilization time for inner loop variables is lesser than the intermediate loop variables because of the three-loop-control design methodology . The control...adaptive design . Control Engineering Practice, 2016. Michael A Bolender and David B Doman. A non -linear model for the longitudinal dynamics of a

Estimating power capability of aged lithium-ion batteries in presence of communication delays

NASA Astrophysics Data System (ADS)

Fridholm, Björn; Wik, Torsten; Kuusisto, Hannes; Klintberg, Anton

2018-04-01

Efficient control of electrified powertrains requires accurate estimation of the power capability of the battery for the next few seconds into the future. When implemented in a vehicle, the power estimation is part of a control loop that may contain several networked controllers which introduces time delays that may jeopardize stability. In this article, we present and evaluate an adaptive power estimation method that robustly can handle uncertain health status and time delays. A theoretical analysis shows that stability of the closed loop system can be lost if the resistance of the model is under-estimated. Stability can, however, be restored by filtering the estimated power at the expense of slightly reduced bandwidth of the signal. The adaptive algorithm is experimentally validated in lab tests using an aged lithium-ion cell subject to a high power load profile in temperatures from -20 to +25 °C. The upper voltage limit was set to 4.15 V and the lower voltage limit to 2.6 V, where significant non-linearities are occurring and the validity of the model is limited. After an initial transient when the model parameters are adapted, the prediction accuracy is within ± 2 % of the actually available power.

Performance constraints and compensation for teleoperation with delay

NASA Technical Reports Server (NTRS)

Mclaughlin, J. S.; Staunton, B. D.

1989-01-01

A classical control perspective is used to characterize performance constraints and evaluate compensation techniques for teleoperation with delay. Use of control concepts such as open and closed loop performance, stability, and bandwidth yield insight to the delay problem. Teleoperator performance constraints are viewed as an open loop time delay lag and as a delay-induced closed loop bandwidth constraint. These constraints are illustrated with a simple analytical tracking example which is corroborated by a real time, 'man-in-the-loop' tracking experiment. The experiment also provides insight to those controller characteristics which are unique to a human operator. Predictive displays and feedforward commands are shown to provide open loop compensation for delay lag. Low pass filtering of telemetry or feedback signals is interpreted as closed loop compensation used to maintain a sufficiently low bandwidth for stability. A new closed loop compensation approach is proposed that uses a reactive (or force feedback) hand controller to restrict system bandwidth by impeding operator inputs.

Closed Loop Control of Oxygen Delivery and Oxygen Generation

DTIC Science & Technology

2017-08-01

AFRL-SA-WP-SR-2017-0024 Closed Loop Control of Oxygen Delivery and Oxygen Generation Dr. Jay Johannigman1, Richard Branson1...for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO...TITLE AND SUBTITLE Closed Loop Control of Oxygen Delivery and Oxygen Generation 5a. CONTRACT NUMBER FA8650-10-2-6140 5b. GRANT NUMBER

Adaptive Backstepping-Based Neural Tracking Control for MIMO Nonlinear Switched Systems Subject to Input Delays.

PubMed

Niu, Ben; Li, Lu

2018-06-01

This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Nonlinear model predictive control for chemical looping process

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

Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng

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

Closed loop deep brain stimulation: an evolving technology.

PubMed

Hosain, Md Kamal; Kouzani, Abbas; Tye, Susannah

2014-12-01

Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.

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.

Preliminary demonstration of a robust controller design method

NASA Technical Reports Server (NTRS)

Anderson, L. R.

1980-01-01

Alternative computational procedures for obtaining a feedback control law which yields a control signal based on measurable quantitites are evaluated. The three methods evaluated are: (1) the standard linear quadratic regulator design model; (2) minimization of the norm of the feedback matrix, k via nonlinear programming subject to the constraint that the closed loop eigenvalues be in a specified domain in the complex plane; and (3) maximize the angles between the closed loop eigenvectors in combination with minimizing the norm of K also via the constrained nonlinear programming. The third or robust design method was chosen to yield a closed loop system whose eigenvalues are insensitive to small changes in the A and B matrices. The relationship between orthogonality of closed loop eigenvectors and the sensitivity of closed loop eigenvalues is described. Computer programs are described.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

PubMed

Zhang, Jin-Xi; Yang, Guang-Hong

2018-05-01

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

Simple robust control laws for robot manipulators. Part 2: Adaptive case

NASA Technical Reports Server (NTRS)

Bayard, D. S.; Wen, J. T.

1987-01-01

A new class of asymptotically stable adaptive control laws is introduced for application to the robotic manipulator. Unlike most applications of adaptive control theory to robotic manipulators, this analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and utilizes a parameterization based on physical (time-invariant) quantities. This approach is made possible by using energy-like Lyapunov functions which retain the nonlinear character and structure of the dynamics, rather than simple quadratic forms which are ubiquitous to the adaptive control literature, and which have bound the theory tightly to linear systems with unknown parameters. It is a unique feature of these results that the adaptive forms arise by straightforward certainty equivalence adaptation of their nonadaptive counterparts found in the companion to this paper (i.e., by replacing unknown quantities by their estimates) and that this simple approach leads to asymptotically stable closed-loop adaptive systems. Furthermore, it is emphasized that this approach does not require convergence of the parameter estimates (i.e., via persistent excitation), invertibility of the mass matrix estimate, or measurement of the joint accelerations.

Hypoglycaemia incidence and recovery during home use of hybrid closed-loop insulin delivery in adults with type 1 diabetes.

PubMed

Ruan, Yue; Bally, Lia; Thabit, Hood; Leelarathna, Lalantha; Hartnell, Sara; Tauschmann, Martin; Wilinska, Malgorzata E; Evans, Mark L; Mader, Julia K; Kojzar, Harald; Dellweg, Sibylle; Benesch, Carsten; Arnolds, Sabine; Pieber, Thomas R; Hovorka, Roman

2018-03-25

Glucose excursion was assessed prior to and post hypoglycaemia to increase understanding of hypoglycaemia incidence and recovery during hybrid closed-loop insulin delivery. We retrospectively analysed data from 60 adults with type 1 diabetes who received, in a crossover randomized design, day-and-night hybrid closed-loop insulin delivery and insulin pump therapy, the latter with or without real-time continuous glucose monitoring. Over 4-week study periods, we identified hypoglycaemic episodes, defined as sensor glucose <3.0 mmol/L, and analysed sensor glucose relative to the onset of hypoglycaemia. We identified 377 hypoglycaemic episodes during hybrid closed-loop intervention vs 662 during control intervention (P < .001), with a predominant reduction of nocturnal hypoglycaemia. The slope of sensor glucose prior to hypoglycaemia was steeper during closed-loop intervention than during control intervention (P < .01), while insulin delivery was reduced (P < .01). During both day and night, participants recovered from hypoglycaemia faster when treated by closed-loop intervention. At 120 minutes post hypoglycaemia, sensor glucose levels were higher during closed-loop intervention compared to the control period (P < .05). In conclusion, closed-loop intervention reduces the risk of hypoglycaemia, particularly overnight, with swift recovery from hypoglycaemia leading to higher 2-hour post-hypoglycaemia glucose levels. © 2018 John Wiley & Sons Ltd.

Adaptive back-stepping control of the harmonic drive system with LuGre model-based friction compensation

NASA Astrophysics Data System (ADS)

Liu, Sen; Gang, Tieqiang

2018-03-01

Harmonic drives are widely used in aerospace and industrial robots. Flexibility, friction and parameter uncertainty will result in transmission performance degradation. In this paper, an adaptive back-stepping method with friction compensation is proposed to improve the tracking performance of the harmonic drive system. The nonlinear friction is described by LuGre model and compensated with a friction observer, and the uncertainty of model parameters is resolved by adaptive parameter estimation method. By using Lyapunov stability theory, it is proved that all the errors of the closed-loop system are uniformly ultimately bounded. Simulations illustrate the effectiveness of our friction compensation method.

Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique.

PubMed

Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong

2016-09-01

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.

Insulin delivery and nocturnal glucose control in children and adolescents with type 1 diabetes.

PubMed

Tauschmann, Martin; Hovorka, Roman

2017-12-01

Nocturnal glucose control remains challenging in children and adolescents with type 1 diabetes due to highly variable overnight insulin requirements. The issue may be addressed by glucose responsive insulin delivery based on real-time continuous glucose measurements. Areas covered: This review outlines recent developments of glucose responsive insulin delivery systems from a paediatric perspective. We cover threshold-based suspend application, predictive low glucose suspend, and more advanced single hormone and dual-hormone closed-loop systems. Approaches are evaluated in relation to nocturnal glucose control particularly during outpatient randomised controlled trials. Expert opinion: Significant progress translating research from controlled clinical centre settings to free-living unsupervised home studies have been achieved over the past decade. Nocturnal glycaemic control can be improved whilst reducing the risk of hypoglycaemia with closed-loop systems. Following the US regulatory approval of the first hybrid closed-loop system in non-paediatric population, large multinational closed-loop clinical trials and pivotal studies including paediatric populations are underway or in preparation to facilitate the use of closed-loop systems in clinical practice.

Closed-Loop HIRF Experiments Performed on a Fault Tolerant Flight Control Computer

NASA Technical Reports Server (NTRS)

Belcastro, Celeste M.

1997-01-01

ABSTRACT Closed-loop HIRF experiments were performed on a fault tolerant flight control computer (FCC) at the NASA Langley Research Center. The FCC used in the experiments was a quad-redundant flight control computer executing B737 Autoland control laws. The FCC was placed in one of the mode-stirred reverberation chambers in the HIRF Laboratory and interfaced to a computer simulation of the B737 flight dynamics, engines, sensors, actuators, and atmosphere in the Closed-Loop Systems Laboratory. Disturbances to the aircraft associated with wind gusts and turbulence were simulated during tests. Electrical isolation between the FCC under test and the simulation computer was achieved via a fiber optic interface for the analog and discrete signals. Closed-loop operation of the FCC enabled flight dynamics and atmospheric disturbances affecting the aircraft to be represented during tests. Upset was induced in the FCC as a result of exposure to HIRF, and the effect of upset on the simulated flight of the aircraft was observed and recorded. This paper presents a description of these closed- loop HIRF experiments, upset data obtained from the FCC during these experiments, and closed-loop effects on the simulated flight of the aircraft.

Closed-loop model identification of cooperative manipulators holding deformable objects

NASA Astrophysics Data System (ADS)

Alkathiri, A. A.; Akmeliawati, R.; Azlan, N. Z.

2017-11-01

This paper presents system identification to obtain the closed-loop models of a couple of cooperative manipulators in a system, which function to hold deformable objects. The system works using the master-slave principle. In other words, one of the manipulators is position-controlled through encoder feedback, while a force sensor gives feedback to the other force-controlled manipulator. Using the closed-loop input and output data, the closed-loop models, which are useful for model-based control design, are estimated. The criteria for model validation are a 95% fit between the measured and simulated output of the estimated models and residual analysis. The results show that for both position and force control respectively, the fits are 95.73% and 95.88%.

An Environmental for Hardware-in-the-Loop Formation Navigation and Control

NASA Technical Reports Server (NTRS)

Burns, Rich; Naasz, Bo; Gaylor, Dave; Higinbotham, John

2004-01-01

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Test Bed (FFTB) at NASA Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the inclusion of GPS receiver hardware in the simulation loop. Support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented.

Fundamental Physics and Practical Applications of Electromagnetic Local Flow Control in High Speed Flows (Rutgers)

DTIC Science & Technology

2010-02-16

field. Techniques utilizing this design use an open- loop control and no flow monitoring sensors are required. Conversely, reactive (or closed - loop ...and closed (dashed line) configuration. 38 closed configuration described above, the ambiguity in the critical limits of the transition...flow; a new vortex is then shed from the cavity leading edge, closing the feedback loop .[31] Open cavities with an L/D approximately greater than

A training rule which guarantees finite-region stability for a class of closed-loop neural-network control systems.

PubMed

Kuntanapreeda, S; Fullmer, R R

1996-01-01

A training method for a class of neural network controllers is presented which guarantees closed-loop system stability. The controllers are assumed to be nonlinear, feedforward, sampled-data, full-state regulators implemented as single hidden-layer neural networks. The controlled systems must be locally hermitian and observable. Stability of the closed-loop system is demonstrated by determining a Lyapunov function, which can be used to identify a finite stability region about the regulator point.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.

PubMed

Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem

2015-03-01

This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Closed-loop control of zebrafish response using a bioinspired robotic-fish in a preference test

PubMed Central

Kopman, Vladislav; Laut, Jeffrey; Polverino, Giovanni; Porfiri, Maurizio

2013-01-01

In this paper, we study the response of zebrafish to a robotic-fish whose morphology and colour pattern are inspired by zebrafish. Experiments are conducted in a three-chambered instrumented water tank where a robotic-fish is juxtaposed with an empty compartment, and the preference of live subjects is scored as the mean time spent in the vicinity of the tank's two lateral sides. The tail-beating of the robotic-fish is controlled in real-time based on feedback from fish motion to explore a spectrum of closed-loop systems, including proportional and integral controllers. Closed-loop control systems are complemented by open-loop strategies, wherein the tail-beat of the robotic-fish is independent of the fish motion. The preference space and the locomotory patterns of fish for each experimental condition are analysed and compared to understand the influence of real-time closed-loop control on zebrafish response. The results of this study show that zebrafish respond differently to the pattern of tail-beating motion executed by the robotic-fish. Specifically, the preference and behaviour of zebrafish depend on whether the robotic-fish tail-beating frequency is controlled as a function of fish motion and how such closed-loop control is implemented. PMID:23152102

Antenna Linear-Quadratic-Gaussian (LQG) Controllers: Properties, Limits of Performance, and Tuning Procedure

NASA Technical Reports Server (NTRS)

Gawronski, W.

2004-01-01

Wind gusts are the main disturbances that depreciate tracking precision of microwave antennas and radiotelescopes. The linear-quadratic-Gaussian (LQG) controllers - as compared with the proportional-and-integral (PI) controllers significantly improve the tracking precision in wind disturbances. However, their properties have not been satisfactorily understood; consequently, their tuning is a trial-and-error process. A control engineer has two tools to tune an LQG controller: the choice of coordinate system of the controller model and the selection of weights of the LQG performance index. This article analyzes properties of an open- and closed-loop antenna. It shows that the proper choice of coordinates of the open-loop model simplifies the shaping of the closed-loop performance. The closed-loop properties are influenced by the LQG weights. The article shows the impact of the weights on the antenna closed-loop bandwidth, disturbance rejection properties, and antenna acceleration. The bandwidth and the disturbance rejection characterize the antenna performance, while the acceleration represents the performance limit set by the antenna hardware (motors). The article presents the controller tuning procedure, based on the coordinate selection and the weight properties. The procedure rationally shapes the closed-loop performance, as an alternative to the trial-and-error approach.

Novel imaging closed loop control strategy for heliostats

NASA Astrophysics Data System (ADS)

Bern, Gregor; Schöttl, Peter; Heimsath, Anna; Nitz, Peter

2017-06-01

Central Receiver Systems use up to thousands of heliostats to concentrate solar radiation. The precise control of heliostat aiming points is crucial not only for efficiency but also for reliable plant operation. Besides the calibration of open loop control systems, closed loop tracking strategies are developed to address a precise and efficient aiming strategy. The need for cost reductions in the heliostat field intensifies the motivation for economic closed loop control systems. This work introduces an approach for a closed loop heliostat tracking strategy using image analysis and signal modulation. The approach aims at the extraction of heliostat focal spot position within the receiver domain by means of a centralized remote vision system decoupled from the rough conditions close to the focal area. Taking an image sequence of the receiver while modulating a signal on different heliostats, their aiming points are retrieved. The work describes the methodology and shows first results from simulations and practical tests performed in small scale, motivating further investigation and deployment.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

Liquid uranium alloy-helium fission reactor

DOEpatents

Minkov, V.

1984-06-13

This invention describes a nuclear fission reactor which has a core vessel and at least one tandem heat exchanger vessel coupled therewith across upper and lower passages to define a closed flow loop. Nuclear fuel such as a uranium alloy in its liquid phase fills these vessels and flow passages. Solid control elements in the reactor core vessel are adapted to be adjusted relative to one another to control fission reaction of the liquid fuel therein. Moderator elements in the other vessel and flow passages preclude fission reaction therein. An inert gas such as helium is bubbled upwardly through the heat exchanger vessel operable to move the liquid fuel upwardly therein and unidirectionally around the closed loop and downwardly through the core vessel. This helium gas is further directed to heat conversion means outside of the reactor vessels to utilize the heat from the fission reaction to generate useful output. The nuclear fuel operates in the 1200 to 1800/sup 0/C range, and even higher to 2500/sup 0/C.

Active vibration suppression of self-excited structures using an adaptive LMS algorithm

NASA Astrophysics Data System (ADS)

Danda Roy, Indranil

The purpose of this investigation is to study the feasibility of an adaptive feedforward controller for active flutter suppression in representative linear wing models. The ability of the controller to suppress limit-cycle oscillations in wing models having root springs with freeplay nonlinearities has also been studied. For the purposes of numerical simulation, mathematical models of a rigid and a flexible wing structure have been developed. The rigid wing model is represented by a simple three-degree-of-freedom airfoil while the flexible wing is modelled by a multi-degree-of-freedom finite element representation with beam elements for bending and rod elements for torsion. Control action is provided by one or more flaps attached to the trailing edge and extending along the entire wing span for the rigid model and a fraction of the wing span for the flexible model. Both two-dimensional quasi-steady aerodynamics and time-domain unsteady aerodynamics have been used to generate the airforces in the wing models. An adaptive feedforward controller has been designed based on the filtered-X Least Mean Squares (LMS) algorithm. The control configuration for the rigid wing model is single-input single-output (SISO) while both SISO and multi-input multi-output (MIMO) configurations have been applied on the flexible wing model. The controller includes an on-line adaptive system identification scheme which provides the LMS controller with a reasonably accurate model of the plant. This enables the adaptive controller to track time-varying parameters in the plant and provide effective control. The wing models in closed-loop exhibit highly damped responses at airspeeds where the open-loop responses are destructive. Simulations with the rigid and the flexible wing models in a time-varying airstream show a 63% and 53% increase, respectively, over their corresponding open-loop flutter airspeeds. The ability of the LMS controller to suppress wing store flutter in the two models has also been investigated. With 10% measurement noise introduced in the flexible wing model, the controller demonstrated good robustness to the extraneous disturbances. In the examples studied it is found that adaptation is rapid enough to successfully control flutter at accelerations in the airstream of up to 15 ft/sec2 for the rigid wing model and 9 ft/sec2 for the flexible wing model.

Real Time Metrology Using Heterodyne Interferometry

NASA Astrophysics Data System (ADS)

Evans, Joseph T..., Jr.

1983-11-01

The Air Force Weapons Laboratory (AFWL) located at Albuquerque, NM has developed a digital heterodyne interferometer capable of real-time, closed loop analysis and control of adaptive optics. The device uses independent phase modulation of two orthogonal polarizations of an argon ion laser to produce a temporally phase modulated interferogram of the test object in a Twyman-Green interferometer. Differential phase detection under the control of a Data General minicomputer helps reconstruct the phase front without noise effects from amplitude modulation in the optical train. The system consists of the interferometer optics, phase detection circuitry, and the minicomputer, allowing for complete software control of the process. The software has been unified into a powerful package that performs automatic data acquisition, OPD reconstruction, and Zernike analysis of the resulting wavefront. The minicomputer has the capability to control external devices so that closed loop analysis and control is possible. New software under development will provide a framework of data acquisition, display, and storage packages which can be integrated with analysis and control packages customized to the user's needs. Preliminary measurements with the system show that it is noise limited by laser beam phase quality and vibration of the optics. Active measures are necessary to reduce the impact of these noise sources.

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.

Closed-Loop Adaptive Optics Control in Strong Atmospheric Turbulence

DTIC Science & Technology

2008-09-01

115 7.1.1 Kalman estimation of anisoplanatic Zernike tilt . . . . 115 7.1.2 An improved temporally phase-shifted design . . . . . 115 7.1.3...5 7. Shack-Hartmann lenslet diagram [40] . . . . . . . . . . . . . . . . . . 9 8. Determining phase tilt from a S-H WFS [8...wavefront prior to it encountering the WFS. In this system a non- deformable mirror known as a fast-steering mirror (FSM) corrects the tilt (average phase

Robust fast controller design via nonlinear fractional differential equations.

PubMed

Zhou, Xi; Wei, Yiheng; Liang, Shu; Wang, Yong

2017-07-01

A new method for linear system controller design is proposed whereby the closed-loop system achieves both robustness and fast response. The robustness performance considered here means the damping ratio of closed-loop system can keep its desired value under system parameter perturbation, while the fast response, represented by rise time of system output, can be improved by tuning the controller parameter. We exploit techniques from both the nonlinear systems control and the fractional order systems control to derive a novel nonlinear fractional order controller. For theoretical analysis of the closed-loop system performance, two comparison theorems are developed for a class of fractional differential equations. Moreover, the rise time of the closed-loop system can be estimated, which facilitates our controller design to satisfy the fast response performance and maintain the robustness. Finally, numerical examples are given to illustrate the effectiveness of our methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Closing the loop of deep brain stimulation

PubMed Central

Carron, Romain; Chaillet, Antoine; Filipchuk, Anton; Pasillas-Lépine, William; Hammond, Constance

2013-01-01

High-frequency deep brain stimulation is used to treat a wide range of brain disorders, like Parkinson's disease. The stimulated networks usually share common electrophysiological signatures, including hyperactivity and/or dysrhythmia. From a clinical perspective, HFS is expected to alleviate clinical signs without generating adverse effects. Here, we consider whether the classical open-loop HFS fulfills these criteria and outline current experimental or theoretical research on the different types of closed-loop DBS that could provide better clinical outcomes. In the first part of the review, the two routes followed by HFS-evoked axonal spikes are explored. In one direction, orthodromic spikes functionally de-afferent the stimulated nucleus from its downstream target networks. In the opposite direction, antidromic spikes prevent this nucleus from being influenced by its afferent networks. As a result, the pathological synchronized activity no longer propagates from the cortical networks to the stimulated nucleus. The overall result can be described as a reversible functional de-afferentation of the stimulated nucleus from its upstream and downstream nuclei. In the second part of the review, the latest advances in closed-loop DBS are considered. Some of the proposed approaches are based on mathematical models, which emphasize different aspects of the parkinsonian basal ganglia: excessive synchronization, abnormal firing-rate rhythms, and a deficient thalamo-cortical relay. The stimulation strategies are classified depending on the control-theory techniques on which they are based: adaptive and on-demand stimulation schemes, delayed and multi-site approaches, stimulations based on proportional and/or derivative control actions, optimal control strategies. Some of these strategies have been validated experimentally, but there is still a large reservoir of theoretical work that may point to ways of improving practical treatment. PMID:24391555

Closing the loop of deep brain stimulation.

PubMed

Carron, Romain; Chaillet, Antoine; Filipchuk, Anton; Pasillas-Lépine, William; Hammond, Constance

2013-12-20

High-frequency deep brain stimulation is used to treat a wide range of brain disorders, like Parkinson's disease. The stimulated networks usually share common electrophysiological signatures, including hyperactivity and/or dysrhythmia. From a clinical perspective, HFS is expected to alleviate clinical signs without generating adverse effects. Here, we consider whether the classical open-loop HFS fulfills these criteria and outline current experimental or theoretical research on the different types of closed-loop DBS that could provide better clinical outcomes. In the first part of the review, the two routes followed by HFS-evoked axonal spikes are explored. In one direction, orthodromic spikes functionally de-afferent the stimulated nucleus from its downstream target networks. In the opposite direction, antidromic spikes prevent this nucleus from being influenced by its afferent networks. As a result, the pathological synchronized activity no longer propagates from the cortical networks to the stimulated nucleus. The overall result can be described as a reversible functional de-afferentation of the stimulated nucleus from its upstream and downstream nuclei. In the second part of the review, the latest advances in closed-loop DBS are considered. Some of the proposed approaches are based on mathematical models, which emphasize different aspects of the parkinsonian basal ganglia: excessive synchronization, abnormal firing-rate rhythms, and a deficient thalamo-cortical relay. The stimulation strategies are classified depending on the control-theory techniques on which they are based: adaptive and on-demand stimulation schemes, delayed and multi-site approaches, stimulations based on proportional and/or derivative control actions, optimal control strategies. Some of these strategies have been validated experimentally, but there is still a large reservoir of theoretical work that may point to ways of improving practical treatment.

Adaptive super twisting vibration control of a flexible spacecraft with state rate estimation

NASA Astrophysics Data System (ADS)

Malekzadeh, Maryam; Karimpour, Hossein

2018-05-01

The robust attitude and vibration control of a flexible spacecraft trying to perform accurate maneuvers in spite of various sources of uncertainty is addressed here. Difficulties for achieving precise and stable pointing arise from noisy onboard sensors, parameters indeterminacy, outer disturbances as well as un-modeled or hidden dynamics interactions. Based on high-order sliding-mode methods, the non-minimum phase nature of the problem is dealt with through output redefinition. An adaptive super-twisting algorithm (ASTA) is incorporated with its observer counterpart on the system under consideration to get reliable attitude and vibration control in the presence of sensor noise and momentum coupling. The closed-loop efficiency is verified through simulations under various indeterminate situations and got compared to other methods.

In-flight results of adaptive attitude control law for a microsatellite

NASA Astrophysics Data System (ADS)

Pittet, C.; Luzi, A. R.; Peaucelle, D.; Biannic, J.-M.; Mignot, J.

2015-06-01

Because satellites usually do not experience large changes of mass, center of gravity or inertia in orbit, linear time invariant (LTI) controllers have been widely used to control their attitude. But, as the pointing requirements become more stringent and the satellite's structure more complex with large steerable and/or deployable appendices and flexible modes occurring in the control bandwidth, one unique LTI controller is no longer sufficient. One solution consists in designing several LTI controllers, one for each set point, but the switching between them is difficult to tune and validate. Another interesting solution is to use adaptive controllers, which could present at least two advantages: first, as the controller automatically and continuously adapts to the set point without changing the structure, no switching logic is needed in the software; second, performance and stability of the closed-loop system can be assessed directly on the whole flight domain. To evaluate the real benefits of adaptive control for satellites, in terms of design, validation and performances, CNES selected it as end-of-life experiment on PICARD microsatellite. This paper describes the design, validation and in-flight results of the new adaptive attitude control law, compared to nominal control law.

A closed-loop neurobotic system for fine touch sensing

NASA Astrophysics Data System (ADS)

Bologna, L. L.; Pinoteau, J.; Passot, J.-B.; Garrido, J. A.; Vogel, J.; Ros Vidal, E.; Arleo, A.

2013-08-01

Objective. Fine touch sensing relies on peripheral-to-central neurotransmission of somesthetic percepts, as well as on active motion policies shaping tactile exploration. This paper presents a novel neuroengineering framework for robotic applications based on the multistage processing of fine tactile information in the closed action-perception loop. Approach. The integrated system modules focus on (i) neural coding principles of spatiotemporal spiking patterns at the periphery of the somatosensory pathway, (ii) probabilistic decoding mechanisms mediating cortical-like tactile recognition and (iii) decision-making and low-level motor adaptation underlying active touch sensing. We probed the resulting neural architecture through a Braille reading task. Main results. Our results on the peripheral encoding of primary contact features are consistent with experimental data on human slow-adapting type I mechanoreceptors. They also suggest second-order processing by cuneate neurons may resolve perceptual ambiguities, contributing to a fast and highly performing online discrimination of Braille inputs by a downstream probabilistic decoder. The implemented multilevel adaptive control provides robustness to motion inaccuracy, while making the number of finger accelerations covariate with Braille character complexity. The resulting modulation of fingertip kinematics is coherent with that observed in human Braille readers. Significance. This work provides a basis for the design and implementation of modular neuromimetic systems for fine touch discrimination in robotics.

Enhanced Performance Controller Design for Stochastic Systems by Adding Extra State Estimation onto the Existing Closed Loop Control

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

Zhou, Yuyang; Zhang, Qichun; Wang, Hong

To enhance the performance of the tracking property , this paper presents a novel control algorithm for a class of linear dynamic stochastic systems with unmeasurable states, where the performance enhancement loop is established based on Kalman filter. Without changing the existing closed loop with the PI controller, the compensative controller is designed to minimize the variances of the tracking errors using the estimated states and the propagation of state variances. Moreover, the stability of the closed-loop systems has been analyzed in the mean-square sense. A simulated example is included to show the effectiveness of the presented control algorithm, wheremore » encouraging results have been obtained.« less

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

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.

Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition.

PubMed

Wang, Wei; Wen, Changyun; Huang, Jiangshuai; Fan, Huijin

2017-11-01

In this paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Closed Loop System Identification with Genetic Algorithms

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2004-01-01

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras

NASA Astrophysics Data System (ADS)

Guo, Dejun; Bourne, Joseph R.; Wang, Hesheng; Yim, Woosoon; Leang, Kam K.

2017-08-01

This paper presents the design and implementation of an adaptive-repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. Applications of this control strategy include the use of high-flying unmanned aerial vehicles (UAVs) with computer vision for monitoring, controlling, and coordinating the movements of lower altitude agents in areas, for example, where GPS signals may be unreliable or nonexistent. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame. Due to the circular motion of the HFV, the resulting motion trajectory of the LFV in the image frame can be periodic in time, thus an adaptive-repetitive control system is exploited for regulation and/or trajectory tracking. The adaptive control law is able to handle uncertainties in the camera's intrinsic and extrinsic parameters. The design and stability analysis of the closed-loop control system is presented, where Lyapunov stability is shown. Simulation and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter, demonstrating the capabilities of the visual-servo control system for localization (i.e.,, motion capturing) and trajectory tracking control. In fact, results show that the LFV can be commanded to hover in place as well as track a user-defined flower-shaped closed trajectory, while the HFV and camera system circulates above with constant angular velocity. On average, the proposed adaptive-repetitive visual-servo control system reduces the average RMS tracking error by over 77% in the image plane and over 71% in the world frame compared to using just the adaptive visual-servo control law.

Mixed H ∞ and Passive Projective Synchronization for Fractional Order Memristor-Based Neural Networks with Time-Delay and Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Song, Xiao-Na; Song, Shuai; Tejado Balsera, Inés; Liu, Lei-Po

2017-10-01

This paper investigates the mixed H ∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks. Our aim is to design a controller such that, though the unavoidable phenomena of time-delay and parameter uncertainty are fully considered, the resulting closed-loop system is asymptotically stable with a mixed H ∞ and passive performance level. By combining active and adaptive control methods, a novel hybrid control strategy is designed, which can guarantee the robust stability of the closed-loop system and also ensure a mixed H ∞ and passive performance level. Via the application of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method. Supported by National Natural Science Foundation of China under Grant Nos. U1604146, U1404610, 61473115, 61203047, Science and Technology Research Project in Henan Province under Grant Nos. 152102210273, 162102410024, and Foundation for the University Technological Innovative Talents of Henan Province under Grant No. 18HASTIT019

Hybrid Closed-Loop Insulin Delivery in Type 1 Diabetes During Supervised Outpatient Conditions.

PubMed

Grosman, Benyamin; Ilany, Jacob; Roy, Anirban; Kurtz, Natalie; Wu, Di; Parikh, Neha; Voskanyan, Gayane; Konvalina, Noa; Mylonas, Chrystaleni; Gottlieb, Rebecca; Kaufman, Francine; Cohen, Ohad

2016-05-01

Efficacy and safety of the Medtronic Hybrid Closed-Loop (HCL) system were tested in subjects with type 1 diabetes in a supervised outpatient setting. The HCL system is a prototype research platform that includes a sensor-augmented insulin pump in communication with a control algorithm housed on an Android-based cellular device. Nine subjects with type 1 diabetes (5 female, mean age 53.3 years, mean A1C 7.2%) underwent 9 studies totaling 571 hours of closed-loop control using either default or personalized parameters. The system required meal announcements with estimates of carbohydrate (CHO) intake that were based on metabolic kitchen quantification (MK), dietician estimates (D), or subject estimates (Control). Postprandial glycemia was compared for MK, D, and Control meals. The overall sensor glucose mean was 145 ± 43, the overall percentage time in the range 70-180 mg/dL was 80%, the overall percentage time <70 mg/dL was 0.79%. Compared to intervals of default parameter use (225 hours), intervals of personalized parameter use (346 hours), sensor glucose mean was 158 ± 49 and 137 ± 37 mg/dL (P < .001), respectively, and included more time in range (87% vs 68%) and less time below range (0.54% vs 1.18%). Most subjects underestimated the CHO content of meals, but postprandial glycemia was not significantly different between MK and matched Control meals (P = .16) or between D and matched Control meals (P = .76). There were no episodes of severe hypoglycemia. The HCL system was efficacious and safe during this study. Personally adapted HCL parameters were associated with more time in range and less time below range than default parameters. Accurate estimates of meal CHO did not contribute to improved postprandial glycemia. © 2016 Diabetes Technology Society.

A reductionist approach to the analysis of learning in brain-computer interfaces.

PubMed

Danziger, Zachary

2014-04-01

The complexity and scale of brain-computer interface (BCI) studies limit our ability to investigate how humans learn to use BCI systems. It also limits our capacity to develop adaptive algorithms needed to assist users with their control. Adaptive algorithm development is forced offline and typically uses static data sets. But this is a poor substitute for the online, dynamic environment where algorithms are ultimately deployed and interact with an adapting user. This work evaluates a paradigm that simulates the control problem faced by human subjects when controlling a BCI, but which avoids the many complications associated with full-scale BCI studies. Biological learners can be studied in a reductionist way as they solve BCI-like control problems, and machine learning algorithms can be developed and tested in closed loop with the subjects before being translated to full BCIs. The method is to map 19 joint angles of the hand (representing neural signals) to the position of a 2D cursor which must be piloted to displayed targets (a typical BCI task). An investigation is presented on how closely the joint angle method emulates BCI systems; a novel learning algorithm is evaluated, and a performance difference between genders is discussed.

Closed-loop thrust and pressure profile throttling of a nitrous oxide/hydroxyl-terminated polybutadiene hybrid rocket motor

NASA Astrophysics Data System (ADS)

Peterson, Zachary W.

Hybrid motors that employ non-toxic, non-explosive components with a liquid oxidizer and a solid hydrocarbon fuel grain have inherently safe operating characteristics. The inherent safety of hybrid rocket motors offers the potential to greatly reduce overall operating costs. Another key advantage of hybrid rocket motors is the potential for in-flight shutdown, restart, and throttle by controlling the pressure drop between the oxidizer tank and the injector. This research designed, developed, and ground tested a closed-loop throttle controller for a hybrid rocket motor using nitrous oxide and hydroxyl-terminated polybutadiene as propellants. The research simultaneously developed closed-loop throttle algorithms and lab scale motor hardware to evaluate the fidelity of the throttle simulations and algorithms. Initial open-loop motor tests were performed to better classify system parameters and to validate motor performance values. Deep-throttle open-loop tests evaluated limits of stable thrust that can be achieved on the test hardware. Open-loop tests demonstrated the ability to throttle the motor to less than 10% of maximum thrust with little reduction in effective specific impulse and acoustical stability. Following the open-loop development, closed-loop, hardware-in-the-loop tests were performed. The closed-loop controller successfully tracked prescribed step and ramp command profiles with a high degree of fidelity. Steady-state accuracy was greatly improved over uncontrolled thrust.

Comparison of cardiac output optimization with an automated closed-loop goal-directed fluid therapy versus non standardized manual fluid administration during elective abdominal surgery: first prospective randomized controlled trial.

PubMed

Lilot, Marc; Bellon, Amandine; Gueugnon, Marine; Laplace, Marie-Christine; Baffeleuf, Bruno; Hacquard, Pauline; Barthomeuf, Felicie; Parent, Camille; Tran, Thomas; Soubirou, Jean-Luc; Robinson, Philip; Bouvet, Lionel; Vassal, Olivia; Lehot, Jean-Jacques; Piriou, Vincent

2018-01-27

An intraoperative automated closed-loop system for goal-directed fluid therapy has been successfully tested in silico, in vivo and in a clinical case-control matching. This trial compared intraoperative cardiac output (CO) in patients managed with this closed-loop system versus usual practice in an academic medical center. The closed-loop system was connected to a CO monitoring system and delivered automated colloid fluid boluses. Moderate to high-risk abdominal surgical patients were randomized either to the closed-loop or the manual group. Intraoperative final CO was the primary endpoint. Secondary endpoints were intraoperative overall mean cardiac index (CI), increase from initial to final CI, intraoperative fluid volume and postoperative outcomes. From January 2014 to November 2015, 46 patients were randomized. There was a lower initial CI (2.06 vs. 2.51 l min -1 m -2 , p = 0.042) in the closed-loop compared to the control group. No difference in final CO and in overall mean intraoperative CI was observed between groups. A significant relative increase from initial to final CI values was observed in the closed-loop but not the control group (+ 28.6%, p = 0.006 vs. + 1.2%, p = 0.843). No difference was found for intraoperative fluid management and postoperative outcomes between groups. There was no significant impact on the primary study endpoint, but this was found in a context of unexpected lower initial CI in the closed-loop group.Trial registry number ID-RCB/EudraCT: 2013-A00770-45. ClinicalTrials.gov Identifier NCT01950845, date of registration: 17 September 2013.

Method for spinning up a three-axis controlled spacecraft

NASA Technical Reports Server (NTRS)

Vorlicek, Preston L. (Inventor)

1988-01-01

A three-axis controlled spacecraft (1), typically a satellite, is spun up about its roll axis (20) prior to firing a motor (2), i.e., a perigee kick motor, to achieve the requisite degree of angular momentum stiffness. Thrusters (21) for imparting rotation about the roll axis (20) are activated in open-loop fashion, typically at less than full duty cycle. Cross-axis torques induced by this rotational motion are compensated for by means of closed control loops for each of the pitch and yaw axes (30, 40, respectively). Each closed control loop combines a prebias torque (72) with torques (75, 74) representative of position and rate feedback information, respectively. A deadband (52) within each closed control loop can be widened during the spinup, to conserve fuel. Position feedback information (75) in each of the control loops is disabled upon saturation of the gyroscope associated with the roll axis (20).

A Method for Precision Closed-Loop Irrigation Using a Modified PID Control Algorithm

NASA Astrophysics Data System (ADS)

Goodchild, Martin; Kühn, Karl; Jenkins, Malcolm; Burek, Kazimierz; Dutton, Andrew

2016-04-01

The benefits of closed-loop irrigation control have been demonstrated in grower trials which show the potential for improved crop yields and resource usage. Managing water use by controlling irrigation in response to soil moisture changes to meet crop water demands is a popular approach but requires knowledge of closed-loop control practice. In theory, to obtain precise closed-loop control of a system it is necessary to characterise every component in the control loop to derive the appropriate controller parameters, i.e. proportional, integral & derivative (PID) parameters in a classic PID controller. In practice this is often difficult to achieve. Empirical methods are employed to estimate the PID parameters by observing how the system performs under open-loop conditions. In this paper we present a modified PID controller, with a constrained integral function, that delivers excellent regulation of soil moisture by supplying the appropriate amount of water to meet the needs of the plant during the diurnal cycle. Furthermore, the modified PID controller responds quickly to changes in environmental conditions, including rainfall events which can result in: controller windup, under-watering and plant stress conditions. The experimental work successfully demonstrates the functionality of a constrained integral PID controller that delivers robust and precise irrigation control. Coir substrate strawberry growing trial data is also presented illustrating soil moisture control and the ability to match water deliver to solar radiation.

Calibration of force actuators on an adaptive secondary prototype.

PubMed

Ricci, Davide; Riccardi, Armando; Zanotti, Daniela

2008-07-10

In the context of the Large Binocular Telescope project, we present the results of force actuator calibrations performed on an adaptive secondary prototype called P45, a thin deformable glass with magnets glued onto its back. Electromagnetic actuators, controlled in a closed loop with a system of internal metrology based on capacitive sensors, continuously deform its shape to correct the distortions of the wavefront. Calibrations of the force actuators are needed because of the differences between driven forces and measured forces. We describe the calibration procedures and the results, obtained with errors of less than 1.5%.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Design of adaptive control systems by means of self-adjusting transversal filters

NASA Technical Reports Server (NTRS)

Merhav, S. J.

1986-01-01

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure.

PubMed

Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan

2014-11-01

This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

An Environment for Hardware-in-the-Loop Formation Navigation and Control Simulation

NASA Technical Reports Server (NTRS)

Burns, Rich

2004-01-01

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Testbed (FFTB) at NASA's Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the injection of GPS receiver hardware into the simulation loop, and support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described in detail. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described in detail. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented and results are analyzed.

Indirect Identification of Linear Stochastic Systems with Known Feedback Dynamics

NASA Technical Reports Server (NTRS)

Huang, Jen-Kuang; Hsiao, Min-Hung; Cox, David E.

1996-01-01

An algorithm is presented for identifying a state-space model of linear stochastic systems operating under known feedback controller. In this algorithm, only the reference input and output of closed-loop data are required. No feedback signal needs to be recorded. The overall closed-loop system dynamics is first identified. Then a recursive formulation is derived to compute the open-loop plant dynamics from the identified closed-loop system dynamics and known feedback controller dynamics. The controller can be a dynamic or constant-gain full-state feedback controller. Numerical simulations and test data of a highly unstable large-gap magnetic suspension system are presented to demonstrate the feasibility of this indirect identification method.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Flatness-based embedded adaptive fuzzy control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

In this paper nonlinear embedded control for turbocharged Diesel engines is developed with the use of Differential flatness theory and adaptive fuzzy control. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances an adaptive fuzzy control scheme is implemanted making use of the transformed dynamical system of the diesel engine that is obtained through the application of differential flatness theory. Since only the system's output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for neuro-fuzzy approximators, which are part of the controller, so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed observer-based adaptive fuzzy control scheme results in H∞ tracking performance.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Based on interval type-2 fuzzy-neural network direct adaptive sliding mode control for SISO nonlinear systems

NASA Astrophysics Data System (ADS)

Lin, Tsung-Chih

2010-12-01

In this paper, a novel direct adaptive interval type-2 fuzzy-neural tracking control equipped with sliding mode and Lyapunov synthesis approach is proposed to handle the training data corrupted by noise or rule uncertainties for nonlinear SISO nonlinear systems involving external disturbances. By employing adaptive fuzzy-neural control theory, the update laws will be derived for approximating the uncertain nonlinear dynamical system. In the meantime, the sliding mode control method and the Lyapunov stability criterion are incorporated into the adaptive fuzzy-neural control scheme such that the derived controller is robust with respect to unmodeled dynamics, external disturbance and approximation errors. In comparison with conventional methods, the advocated approach not only guarantees closed-loop stability but also the output tracking error of the overall system will converge to zero asymptotically without prior knowledge on the upper bound of the lumped uncertainty. Furthermore, chattering effect of the control input will be substantially reduced by the proposed technique. To illustrate the performance of the proposed method, finally simulation example will be given.

DC servomechanism parameter identification: a Closed Loop Input Error approach.

PubMed

Garrido, Ruben; Miranda, Roger

2012-01-01

This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis and design of a 3rd order velocity-controlled closed-loop for MEMS vibratory gyroscopes.

PubMed

Wu, Huan-ming; Yang, Hai-gang; Yin, Tao; Jiao, Ji-wei

2013-09-18

The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when the control loop reaches to 3rd order. In this paper, we propose a linearization design approach to overcome this limitation by establishing a 3rd order linear model of the control loop and transferring the analysis to the frequency domain. Order reduction is applied on the built linear model's transfer function by constructing a zero-pole doublet, and therefore mathematical expression of each control loop's performance specification is obtained. Then an optimization methodology is summarized, which reveals that a robust, stable and swift control loop can be achieved by carefully selecting the system parameters following a priority order. Closed-loop drive circuits are designed and implemented using 0.35 μm complementary metal oxide semiconductor (CMOS) process, and experiments carried out on a gyroscope prototype verify the optimization methodology that an optimized stability of the control loop can be achieved by constructing the zero-pole doublet, and disturbance rejection capability (D.R.C) of the control loop can be improved by increasing the integral term.

Experimental verification of a real-time tuning method of a model-based controller by perturbations to its poles

NASA Astrophysics Data System (ADS)

Kajiwara, Itsuro; Furuya, Keiichiro; Ishizuka, Shinichi

2018-07-01

Model-based controllers with adaptive design variables are often used to control an object with time-dependent characteristics. However, the controller's performance is influenced by many factors such as modeling accuracy and fluctuations in the object's characteristics. One method to overcome these negative factors is to tune model-based controllers. Herein we propose an online tuning method to maintain control performance for an object that exhibits time-dependent variations. The proposed method employs the poles of the controller as design variables because the poles significantly impact performance. Specifically, we use the simultaneous perturbation stochastic approximation (SPSA) to optimize a model-based controller with multiple design variables. Moreover, a vibration control experiment of an object with time-dependent characteristics as the temperature is varied demonstrates that the proposed method allows adaptive control and stably maintains the closed-loop characteristics.

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 heat pump and battery storage demand side energy management

NASA Astrophysics Data System (ADS)

Sobieczky, Florian; Lettner, Christian; Natschläger, Thomas; Traxler, Patrick

2017-11-01

An adaptive linear model predictive control strategy is introduced for the problem of demand side energy management, involving a photovoltaic device, a battery, and a heat pump. Moreover, the heating influence of solar radiation via the glass house effect is considered. Global sunlight radiation intensity and the outside temperature are updated by weather forecast data. The identification is carried out after adapting to a time frame witch sufficiently homogeneous weather. In this way, in spite of the linearity an increase in precision and cost reduction of up to 46% is achieved. It is validated for an open and closed loop version of the MPC problem using real data of the ambient temperature and the global radiation.

Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

PubMed

Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

2011-05-27

Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

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.

Non-linear control of a hydraulic piezo-valve using a generalised Prandtl-Ishlinskii hysteresis model

NASA Astrophysics Data System (ADS)

Stefanski, Frederik; Minorowicz, Bartosz; Persson, Johan; Plummer, Andrew; Bowen, Chris

2017-01-01

The potential to actuate proportional flow control valves using piezoelectric ceramics or other smart materials has been investigated for a number of years. Although performance advantages compared to electromagnetic actuation have been demonstrated, a major obstacle has proven to be ferroelectric hysteresis, which is typically 20% for a piezoelectric actuator. In this paper, a detailed study of valve control methods incorporating hysteresis compensation is made for the first time. Experimental results are obtained from a novel spool valve actuated by a multi-layer piezoelectric ring bender. A generalised Prandtl-Ishlinskii model, fitted to experimental training data from the prototype valve, is used to model hysteresis empirically. This form of model is analytically invertible and is used to compensate for hysteresis in the prototype valve both open loop, and in several configurations of closed loop real time control system. The closed loop control configurations use PID (Proportional Integral Derivative) control with either the inverse hysteresis model in the forward path or in a command feedforward path. Performance is compared to both open and closed loop control without hysteresis compensation via step and frequency response results. Results show a significant improvement in accuracy and dynamic performance using hysteresis compensation in open loop, but where valve position feedback is available for closed loop control the improvements are smaller, and so conventional PID control may well be sufficient. It is concluded that the ability to combine state-of-the-art multi-layer piezoelectric bending actuators with either sophisticated hysteresis compensation or closed loop control provides a route for the creation of a new generation of high performance piezoelectric valves.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

NASA Astrophysics Data System (ADS)

Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

2018-03-01

In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

Closed Loop Vibrational Control: Theory and Applications

DTIC Science & Technology

1993-10-01

the open loop system dynamics will be close to that of Bit. However, in general, in a closed loop system with a specified feedback co-’ - oller , for...Juang, and G. Rodriguez , "Formulations and Applications of Large Structure Actuator and Sensor Placements," Second VPI & SU/AIAA Symposium on Dynamics

Similarity Metrics for Closed Loop Dynamic Systems

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Yang, Lee C.; Bedrossian, Naz; Hall, Robert A.

2008-01-01

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Development of closed loop roll control for magnetic balance systems

NASA Technical Reports Server (NTRS)

Covert, E. E.; Haldeman, C. W.; Ramohalli, G.; Way, P.

1982-01-01

This research was undertaken with the goal of demonstrating closed loop control of the roll degree of freedom on the NASA prototype magnetic suspension and balance system at the MIT Aerophysics Laboratory, thus, showing feasibility for a roll control system for any large magnetic balance system which might be built in the future. During the research under this grant, study was directed toward the several areas of torque generation, position sensing, model construction and control system design. These effects were then integrated to produce successful closed loop operation of the analogue roll control system. This experience indicated the desirability of microprocessor control for the angular degrees of freedom.

On the feasibility of closed-loop control of intra-aortic balloon pumping

NASA Technical Reports Server (NTRS)

Clark, J. W., Jr.; Bourland, H. M.; Kane, G. R.

1973-01-01

A closed-loop control scheme for the control of intra-aortic balloon pumping has been developed and tested in dog experiments. A performance index reflecting the general objectives of balloon-assist pumping is developed and a modified steepest ascent control algorithm is utilized for the selection of a proper operating point for the balloon during its pumping cycle. This paper attempts to indicate the feasibility of closed-loop control of balloon pumping, and particularly its flexibility in achieving both diastolic augmentation of mean aortic pressure and control of the level of end-diastolic pressure (EDP) an important factor in reducing heart work.

Innovations in Rheometer Controlled-Rate Control Loop Design: Ultra Low Angular Speed Control and New Applications

NASA Astrophysics Data System (ADS)

Schulz, Ulrich; Sierro, Philippe; Nijman, Jint

2008-07-01

The design and implementation of an angular speed control loop for a universal rheometer is not a trivial task. The combination of a highly dynamic, very low inertia (drag cup) motor (motor inertia is 10-5 kg m2) with samples which can range in viscosity from 10-3 Pas to 108 Pas, which can be between purely viscous and higly viscoelastic, which can exhibit yield-stresses, etc. asks for a highly adaptive digital control loop. For the HAAKE MARS rotational rheometer a new adaptive control loop was developed which allows the control of angular speeds as low 5×10-9 rad/s and response times a short as 10 ms. The adaptation of the control loop to "difficult" samples is performed by analysing the response of the complete system to a short pre-test. In this paper we will show that the (very) short response times at (very) low angular speeds are not only achieved with ideal samples, but due to the adaptable control loop, also with "difficult" samples. We will show measurement results on "difficult" samples like cosmetic creams and emulsions, a laponite gel, etc. to proof that angular speeds down to 10-4 rad/s are reached within 10 ms to 20 ms and angular speeds down to 10-7 rad/s within 1 s to 2 s. The response times for reaching ultra low angular speeds down to 5×10-9 rad/s are in the order of 10 s to 30 s. With this new control loop it is, for the first time, possible to measure yield stresses by applying a very low constant shear-rate to the sample and measuring the torque response as a function of time.

Simplified adaptive control of an orbiting flexible spacecraft

NASA Astrophysics Data System (ADS)

Maganti, Ganesh B.; Singh, Sahjendra N.

2007-10-01

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

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

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

PubMed

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

2017-01-01

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

Closed-Loop Process Control for Electron Beam Freeform Fabrication and Deposition Processes

NASA Technical Reports Server (NTRS)

Taminger, Karen M. (Inventor); Hofmeister, William H. (Inventor); Martin, Richard E. (Inventor); Hafley, Robert A. (Inventor)

2013-01-01

A closed-loop control method for an electron beam freeform fabrication (EBF(sup 3)) process includes detecting a feature of interest during the process using a sensor(s), continuously evaluating the feature of interest to determine, in real time, a change occurring therein, and automatically modifying control parameters to control the EBF(sup 3) process. An apparatus provides closed-loop control method of the process, and includes an electron gun for generating an electron beam, a wire feeder for feeding a wire toward a substrate, wherein the wire is melted and progressively deposited in layers onto the substrate, a sensor(s), and a host machine. The sensor(s) measure the feature of interest during the process, and the host machine continuously evaluates the feature of interest to determine, in real time, a change occurring therein. The host machine automatically modifies control parameters to the EBF(sup 3) apparatus to control the EBF(sup 3) process in a closed-loop manner.

Closed-Loop and Activity-Guided Optogenetic Control

PubMed Central

Grosenick, Logan; Marshel, James H.; Deisseroth, Karl

2016-01-01

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals. PMID:25856490

Runtime Assurance Framework Development for Highly Adaptive Flight Control Systems

DTIC Science & Technology

2015-12-01

performing a surveillance mission. The demonstration platform consisted of RTA systems for the inner- loop control, outer- loop guidance, ownship flight...For the inner- loop , the concept of employing multiple transition controllers in the reversionary control system was studied. For all feedback levels...5 RTA Protection Applied to Inner- Loop Control Systems .................................................61 5.1 General Description of Morphing Wing

Automatic control of finite element models for temperature-controlled radiofrequency ablation.

PubMed

Haemmerich, Dieter; Webster, John G

2005-07-14

The finite element method (FEM) has been used to simulate cardiac and hepatic radiofrequency (RF) ablation. The FEM allows modeling of complex geometries that cannot be solved by analytical methods or finite difference models. In both hepatic and cardiac RF ablation a common control mode is temperature-controlled mode. Commercial FEM packages don't support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. We present results of a temperature controlled 3-D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100 degrees C. The closed loop system simulation output closely correlated with the FEM model, and allowed us to optimize control parameters. The closed loop control of the FEM model allowed us to implement temperature controlled RF ablation with minimal user input.

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.

Open-Loop HIRF Experiments Performed on a Fault Tolerant Flight Control Computer

NASA Technical Reports Server (NTRS)

Koppen, Daniel M.

1997-01-01

During the third quarter of 1996, the Closed-Loop Systems Laboratory was established at the NASA Langley Research Center (LaRC) to study the effects of High Intensity Radiated Fields on complex avionic systems and control system components. This new facility provided a link and expanded upon the existing capabilities of the High Intensity Radiated Fields Laboratory at LaRC that were constructed and certified during 1995-96. The scope of the Closed-Loop Systems Laboratory is to place highly integrated avionics instrumentation into a high intensity radiated field environment, interface the avionics to a real-time flight simulation that incorporates aircraft dynamics, engines, sensors, actuators and atmospheric turbulence, and collect, analyze, and model aircraft performance. This paper describes the layout and functionality of the Closed-Loop Systems Laboratory, and the open-loop calibration experiments that led up to the commencement of closed-loop real-time flight experiments.

Distributed Adaptive Containment Control for a Class of Nonlinear Multiagent Systems With Input Quantization.

PubMed

Wang, Chenliang; Wen, Changyun; Hu, Qinglei; Wang, Wei; Zhang, Xiuyu

2018-06-01

This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.

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

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

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

PubMed

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

2010-09-01

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

Closed-loop endo-atmospheric ascent guidance for reusable launch vehicle

NASA Astrophysics Data System (ADS)

Sun, Hongsheng

This dissertation focuses on the development of a closed-loop endo-atmospheric ascent guidance algorithm for the 2nd generation reusable launch vehicle. Special attention has been given to the issues that impact on viability, complexity and reliability in on-board implementation. The algorithm is called once every guidance update cycle to recalculate the optimal solution based on the current flight condition, taking into account atmospheric effects and path constraints. This is different from traditional ascent guidance algorithms which operate in a simple open-loop mode inside atmosphere, and later switch to a closed-loop vacuum ascent guidance scheme. The classical finite difference method is shown to be well suited for fast solution of the constrained optimal three-dimensional ascent problem. The initial guesses for the solutions are generated using an analytical vacuum optimal ascent guidance algorithm. Homotopy method is employed to gradually introduce the aerodynamic forces to generate the optimal solution from the optimal vacuum solution. The vehicle chosen for this study is the Lockheed Martin X-33 lifting-body reusable launch vehicle. To verify the algorithm presented in this dissertation, a series of open-loop and closed-loop tests are performed for three different missions. Wind effects are also studied in the closed-loop simulations. For comparison, the solutions for the same missions are also obtained by two independent optimization softwares. The results clearly establish the feasibility of closed-loop endo-atmospheric ascent guidance of rocket-powered launch vehicles. ATO cases are also tested to assess the adaptability of the algorithm to autonomously incorporate the abort modes.

Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

PubMed

Dai, Shi-Lu; Wang, Cong; Wang, Min

2014-01-01

This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

PubMed Central

Luque, Niceto R.; Garrido, Jesús A.; Carrillo, Richard R.; D'Angelo, Egidio; Ros, Eduardo

2014-01-01

The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network. PMID:25177290

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Structural robustness with suboptimal responses for linear state space model

NASA Technical Reports Server (NTRS)

Keel, L. H.; Lim, Kyong B.; Juang, Jer-Nan

1989-01-01

A relationship between the closed-loop eigenvalues and the amount of perturbations in the open-loop matrix is addressed in the context of performance robustness. If the allowable perturbation ranges of elements of the open-loop matrix A and the desired tolerance of the closed-loop eigenvalues are given such that max(j) of the absolute value of Delta-lambda(j) (A+BF) should be less than some prescribed value, what is a state feedback controller F which satisfies the closed-loop eigenvalue perturbation-tolerance requirement for a class of given perturbation in A? The paper gives an algorithm to design such a controller. Numerical examples are included for illustration.

Miniature Fourier transform spectrometer with a dual closed-loop controlled electrothermal micromirror.

PubMed

Han, Fengtian; Wang, Wei; Zhang, Xiaoyang; Xie, Huikai

2016-10-03

A large piston-displacement electrothermal micromirror with closed-loop control of both piston scan and tilting of the mirror plate is demonstrated for use in a miniature Fourier transform spectrometer. Constant scan velocity in an ultra large piston scan range has been demonstrated by the proposed closed-loop piston control scheme which can be easily implemented without considerably increasing system complexity. The experimental results show that the usable linear scan range generated by the micromirror has been extended up to 505 μm. The measured spectral resolution in a compact spectrometer reaches 20 cm^-1, or 0.57 nm at 532 nm wavelength. Compared to other presented systems, this microspectrometer will benefit from the closed-loop thermal actuator approach utilizing both the piston servo and tilt control to provide more consistent spectral response, improved spectral resolution and enhanced robustness to disturbances.

Comparison of Reconstruction and Control algorithms on the ESO end-to-end simulator OCTOPUS

NASA Astrophysics Data System (ADS)

Montilla, I.; Béchet, C.; Lelouarn, M.; Correia, C.; Tallon, M.; Reyes, M.; Thiébaut, É.

Extremely Large Telescopes are very challenging concerning their Adaptive Optics requirements. Their diameters, the specifications demanded by the science for which they are being designed for, and the planned use of Extreme Adaptive Optics systems, imply a huge increment in the number of degrees of freedom in the deformable mirrors. It is necessary to study new reconstruction algorithms to implement the real time control in Adaptive Optics at the required speed. We have studied the performance, applied to the case of the European ELT, of three different algorithms: the matrix-vector multiplication (MVM) algorithm, considered as a reference; the Fractal Iterative Method (FrIM); and the Fourier Transform Reconstructor (FTR). The algorithms have been tested on ESO's OCTOPUS software, which simulates the atmosphere, the deformable mirror, the sensor and the closed-loop control. The MVM is the default reconstruction and control method implemented in OCTOPUS, but it scales in O(N2) operations per loop so it is not considered as a fast algorithm for wave-front reconstruction and control on an Extremely Large Telescope. The two other methods are the fast algorithms studied in the E-ELT Design Study. The performance, as well as their response in the presence of noise and with various atmospheric conditions, has been compared using a Single Conjugate Adaptive Optics configuration for a 42 m diameter ELT, with a total amount of 5402 actuators. Those comparisons made on a common simulator allow to enhance the pros and cons of the various methods, and give us a better understanding of the type of reconstruction algorithm that an ELT demands.

Adaptive Wavelet Coding Applied in a Wireless Control System.

PubMed

Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O

2017-12-13

Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

Closed-loop and robust control of quantum systems.

PubMed

Chen, Chunlin; Wang, Lin-Cheng; Wang, Yuanlong

2013-01-01

For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H(∞) control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

NASA Astrophysics Data System (ADS)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

Time delay compensation for closed-loop insulin delivery systems: a simulation study.

PubMed

Reboldi, G P; Home, P D; Calabrese, G; Fabietti, P G; Brunetti, P; Massi Benedetti, M

1991-06-01

Closed loop insulin therapy certainly represents the best possible approach to insulin replacement. However, present limitations preclude wider application of the so-called artificial pancreas. Therefore, a thorough understanding of these limitations is needed to design better systems for future long-term use. The present simulation study was design: to obtain better information on the impact of the measurement delay of currently available closed-loop devices both during closed-loop insulin delivery and blood glucose clamp studies, and to design and test a time delay compensator based on the method originally described by O.J. Smith. Simulations were performed on a Compaq Deskpro 486/25 personal computer under MS-DOS operating system using Simnon rel. 3.00 software. There was a direct relationship between measurement delay and amount of insulin delivered, i.e., the longer the delay the higher the insulin dose needed to control a rise in blood glucose; the closed-loop response in presence of a time delay was qualitatively impaired both during insulin delivery and blood glucose clamp studies; time delay compensation was effective in reducing the insulin dose and improving controller stability during the early phase of clamp studies. However, the robustness of a Smith's predictor-based controller should be carefully evaluated before implementation in closed-loop systems can be considered.

A review of implantable biosensors for closed-loop glucose control and other drug delivery applications.

PubMed

Scholten, Kee; Meng, Ellis

2018-06-15

Closed-loop drug delivery promises autonomous control of pharmacotherapy through the continuous monitoring of biomarker levels. For decades, researchers have strived for portable closed-loop systems capable of treating ambulatory patients with chronic conditions such as diabetes mellitus. After years of development, the first of these systems have left the laboratory and entered commercial use. This long-awaited advance reflects recent development of chronically stable implantable biosensors able to accurately measure biomarker levels in vivo. This review discusses the role of implantable biosensors in closed-loop drug delivery applications, with the intent to provide a resource for engineers and researchers studying such systems. We provide an overview of common biosensor designs and review the principle challenges in implementing long indwelling sensors: namely device sensitivity, selectivity, and lifetime. This review examines novel advances in transducer design, biological interface, and material biocompatibility, with a focus on recent academic and commercial work which provide successful strategies to overcome perennial challenges. This review focuses primarily on the topics of closed-loop glucose control and continuous glucose monitoring biosensors, which make up the overwhelming majority of published research in this area. We conclude with an overview of recent advances in closed-loop systems targeting applications outside blood glucose management. Copyright © 2018 Elsevier B.V. All rights reserved.

Inverted Pendulum Standing Apparatus for Investigating Closed-Loop Control of Ankle Joint Muscle Contractions during Functional Electrical Stimulation.

PubMed

Tan, John F; Masani, Kei; Vette, Albert H; Zariffa, José; Robinson, Mark; Lynch, Cheryl; Popovic, Milos R

2014-01-01

The restoration of arm-free standing in individuals with paraplegia can be facilitated via functional electrical stimulation (FES). In developing adequate control strategies for FES systems, it remains challenging to test the performance of a particular control scheme on human subjects. In this study, we propose a testing platform for developing effective control strategies for a closed-loop FES system for standing. The Inverted Pendulum Standing Apparatus (IPSA) is a mechanical inverted pendulum, whose angular position is determined by the subject's ankle joint angle as controlled by the FES system while having the subject's body fixed in a standing frame. This approach provides a setup that is safe, prevents falling, and enables a research and design team to rigorously test various closed-loop controlled FES systems applied to the ankle joints. To demonstrate the feasibility of using the IPSA, we conducted a case series that employed the device for studying FES closed-loop controllers for regulating ankle joint kinematics during standing. The utilized FES system stimulated, in able-bodied volunteers, the plantarflexors as they prevent toppling during standing. Four different conditions were compared, and we were able to show unique performance of each condition using the IPSA. We concluded that the IPSA is a useful tool for developing and testing closed-loop controlled FES systems for regulating ankle joint position during standing.

Inverted Pendulum Standing Apparatus for Investigating Closed-Loop Control of Ankle Joint Muscle Contractions during Functional Electrical Stimulation

PubMed Central

Tan, John F.; Masani, Kei; Vette, Albert H.; Zariffa, José; Robinson, Mark; Lynch, Cheryl; Popovic, Milos R.

2014-01-01

The restoration of arm-free standing in individuals with paraplegia can be facilitated via functional electrical stimulation (FES). In developing adequate control strategies for FES systems, it remains challenging to test the performance of a particular control scheme on human subjects. In this study, we propose a testing platform for developing effective control strategies for a closed-loop FES system for standing. The Inverted Pendulum Standing Apparatus (IPSA) is a mechanical inverted pendulum, whose angular position is determined by the subject's ankle joint angle as controlled by the FES system while having the subject's body fixed in a standing frame. This approach provides a setup that is safe, prevents falling, and enables a research and design team to rigorously test various closed-loop controlled FES systems applied to the ankle joints. To demonstrate the feasibility of using the IPSA, we conducted a case series that employed the device for studying FES closed-loop controllers for regulating ankle joint kinematics during standing. The utilized FES system stimulated, in able-bodied volunteers, the plantarflexors as they prevent toppling during standing. Four different conditions were compared, and we were able to show unique performance of each condition using the IPSA. We concluded that the IPSA is a useful tool for developing and testing closed-loop controlled FES systems for regulating ankle joint position during standing. PMID:27350992

Nonlinear frequency response based adaptive vibration controller design for a class of nonlinear systems

NASA Astrophysics Data System (ADS)

Thenozhi, Suresh; Tang, Yu

2018-01-01

Frequency response functions (FRF) are often used in the vibration controller design problems of mechanical systems. Unlike linear systems, the FRF derivation for nonlinear systems is not trivial due to their complex behaviors. To address this issue, the convergence property of nonlinear systems can be studied using convergence analysis. For a class of time-invariant nonlinear systems termed as convergent systems, the nonlinear FRF can be obtained. The present paper proposes a nonlinear FRF based adaptive vibration controller design for a mechanical system with cubic damping nonlinearity and a satellite system. Here the controller gains are tuned such that a desired closed-loop frequency response for a band of harmonic excitations is achieved. Unlike the system with cubic damping, the satellite system is not convergent, therefore an additional controller is utilized to achieve the convergence property. Finally, numerical examples are provided to illustrate the effectiveness of the proposed controller.

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Correcting highly aberrated eyes using large-stroke adaptive optics.

PubMed

Sabesan, Ramkumar; Ahmad, Kamran; Yoon, Geunyoung

2007-11-01

To investigate the optical performance of a large-stroke deformable mirror in correcting large aberrations in highly aberrated eyes. A large-stroke deformable mirror (Mirao 52D; Imagine Eyes) and a Shack-Hartmann wavefront sensor were used in an adaptive optics system. Closed-loop correction of the static aberrations of a phase plate designed for an advanced keratoconic eye was performed for a 6-mm pupil. The same adaptive optics system was also used to correct the aberrations in one eye each of two moderate keratoconic and three normal human eyes for a 6-mm pupil. With closed-loop correction of the phase plate, the total root-mean-square (RMS) over a 6-mm pupil was reduced from 3.54 to 0.04 microm in 30 to 40 iterations, corresponding to 3 to 4 seconds. Adaptive optics closed-loop correction reduced an average total RMS of 1.73+/-0.998 to 0.10+/-0.017 microm (higher order RMS of 0.39+/-0.124 to 0.06+/-0.004 microm) in the three normal eyes and 2.73+/-1.754 to 0.10+/-0.001 microm (higher order RMS of 1.82+/-1.058 to 0.05+/-0.017 microm) in the two keratoconic eyes. Aberrations in both normal and highly aberrated eyes were successfully corrected using the large-stroke deformable mirror to provide almost perfect optical quality. This mirror can be a powerful tool to assess the limit of visual performance achievable after correcting the aberrations, especially in eyes with abnormal corneal profiles.

HALOS: fast, autonomous, holographic adaptive optics

NASA Astrophysics Data System (ADS)

Andersen, Geoff P.; Gelsinger-Austin, Paul; Gaddipati, Ravi; Gaddipati, Phani; Ghebremichael, Fassil

2014-08-01

We present progress on our holographic adaptive laser optics system (HALOS): a compact, closed-loop aberration correction system that uses a multiplexed hologram to deconvolve the phase aberrations in an input beam. The wavefront characterization is based on simple, parallel measurements of the intensity of fixed focal spots and does not require any complex calculations. As such, the system does not require a computer and is thus much cheaper, less complex than conventional approaches. We present details of a fully functional, closed-loop prototype incorporating a 32-element MEMS mirror, operating at a bandwidth of over 10kHz. Additionally, since the all-optical sensing is made in parallel, the speed is independent of actuator number - running at the same bandwidth for one actuator as for a million.

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

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

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

Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

PubMed Central

Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo

2013-01-01

Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario. PMID:24130518

Closed-loop motor control using high-speed fiber optics

NASA Technical Reports Server (NTRS)

Dawson, Reginald (Inventor); Rodriquiz, Dagobert (Inventor)

1991-01-01

A closed-loop control system for controlling the operation of one or more servo motors or other controllable devices is described. The system employs a fiber optics link immune to electromagnetic interference, for transmission of control signals from a controller or controllers at a remote station to the power electronics located in proximity to the motors or other devices at the local station. At the remote station the electrical control signals are time-multiplexed, converted to a formatted serial bit stream, and converted to light signals for transmission over a single fiber of the fiber optics link. At the local station, the received optical signals are reconstructed as electrical control signals for the controlled motors or other devices. At the local station, an encoder sensor linked to the driven device generates encoded feedback signals which provide information as to a condition of the controlled device. The encoded signals are placed in a formatted serial bit stream, multiplexed, and transmitted as optical signals over a second fiber of the fiber optic link which closes the control loop of the closed-loop motor controller. The encoded optical signals received at the remote station are demultiplexed, reconstructed and coupled to the controller(s) as electrical feedback signals.

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

PubMed

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Optimal and Adaptive Control of Flow in a Thermal Convection Loop

NASA Astrophysics Data System (ADS)

Yuen, Po Ki; Bau, Haim

1998-11-01

In theory and experiment, we use nonlinear and linear optimal and adaptive controllers to suppress the naturally occurring chaotic convection in a thermal convection loop. The thermal convection loop is a simple experimental analog of the Lorenz equations, and it provides a convenient platform for testing and comparing the performance of various control strategies in a fluid mechanical setting. The performance of the optimal and adaptive controllers is compared with that of a previously developed simple feedback controller (Singer, J., Wang, Y., & Bau, H., H., 1991, Physical Review Letters, 66,123-1125.)(Wang, Y., Singer, J., & Bau, H., H., 1992, J. Fluid Mechanics, 237, 479-498.), a nonlinear controller with a cubic nonlinearity(Yuen, P., & Bau, H., H., 1996, J. Fluid Mechanics, 317, 91-109.), and a neural net controller(Yuen, P., & Bau, H., H., 1998, Neural Networks, 11, 557 - 569, 1998.). It is demonstrated that an adaptive controller can perform successfully even when the system's model is not known.

Disturbance rejection performance analyses of closed loop control systems by reference to disturbance ratio.

PubMed

Alagoz, Baris Baykant; Deniz, Furkan Nur; Keles, Cemal; Tan, Nusret

2015-03-01

This study investigates disturbance rejection capacity of closed loop control systems by means of reference to disturbance ratio (RDR). The RDR analysis calculates the ratio of reference signal energy to disturbance signal energy at the system output and provides a quantitative evaluation of disturbance rejection performance of control systems on the bases of communication channel limitations. Essentially, RDR provides a straightforward analytical method for the comparison and improvement of implicit disturbance rejection capacity of closed loop control systems. Theoretical analyses demonstrate us that RDR of the negative feedback closed loop control systems are determined by energy spectral density of controller transfer function. In this manner, authors derived design criteria for specifications of disturbance rejection performances of PID and fractional order PID (FOPID) controller structures. RDR spectra are calculated for investigation of frequency dependence of disturbance rejection capacity and spectral RDR analyses are carried out for PID and FOPID controllers. For the validation of theoretical results, simulation examples are presented. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A concept for adaptive performance optimization on commercial transport aircraft

NASA Technical Reports Server (NTRS)

Jackson, Michael R.; Enns, Dale F.

1995-01-01

An adaptive control method is presented for the minimization of drag during flight for transport aircraft. The minimization of drag is achieved by taking advantage of the redundant control capability available in the pitch axis, with the horizontal tail used as the primary surface and symmetric deflection of the ailerons and cruise flaps used as additional controls. The additional control surfaces are excited with sinusoidal signals, while the altitude and velocity loops are closed with guidance and control laws. A model of the throttle response as a function of the additional control surfaces is formulated and the parameters in the model are estimated from the sensor measurements using a least squares estimation method. The estimated model is used to determine the minimum drag positions of the control surfaces. The method is presented for the optimization of one and two additional control surfaces. The adaptive control method is extended to optimize rate of climb with the throttle fixed. Simulations that include realistic disturbances are presented, as well as the results of a Monte Carlo simulation analysis that shows the effects of changing the disturbance environment and the excitation signal parameters.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Fiber-optic projected-fringe digital interferometry

NASA Technical Reports Server (NTRS)

Mercer, Carolyn R.; Beheim, Glenn

1990-01-01

A phase-stepped projected-fringe interferometer was developed which uses a closed-loop fiber-optic phase-control system to make very accurate surface profile measurements. The closed-loop phase-control system greatly reduces phase-stepping error, which is frequently the dominant source of error in digital interferometers. Two beams emitted from a fiber-optic coupler are combined to form an interference fringe pattern on a diffusely reflecting object. Reflections off of the fibers' output faces are used to create a phase-indicating signal for the closed-loop optical phase controller. The controller steps the phase difference between the two beams by pi/2 radians in order to determine the object's surface profile using a solid-state camera and a computer. The system combines the ease of alignment and automated data reduction of phase-stepping projected-fringe interferometry with the greatly improved phase-stepping accuracy of our closed-loop phase-controller. The system is demonstrated by measuring the profile of a plate containing several convex surfaces whose heights range from 15 to 25 micron high.

A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems

PubMed Central

Wright, James; Macefield, Vaughan G.; van Schaik, André; Tapson, Jonathan C.

2016-01-01

It has been widely recognized that closed-loop neuroprosthetic systems achieve more favorable outcomes for users then equivalent open-loop devices. Improved performance of tasks, better usability, and greater embodiment have all been reported in systems utilizing some form of feedback. However, the interdisciplinary work on neuroprosthetic systems can lead to miscommunication due to similarities in well-established nomenclature in different fields. Here we present a review of control strategies in existing experimental, investigational and clinical neuroprosthetic systems in order to establish a baseline and promote a common understanding of different feedback modes and closed-loop controllers. The first section provides a brief discussion of feedback control and control theory. The second section reviews the control strategies of recent Brain Machine Interfaces, neuromodulatory implants, neuroprosthetic systems, and assistive neurorobotic devices. The final section examines the different approaches to feedback in current neuroprosthetic and neurorobotic systems. PMID:27462202

Robust output feedback stabilization for a flexible marine riser system.

PubMed

Zhao, Zhijia; Liu, Yu; Guo, Fang

2017-12-06

The aim of this paper is to develop a boundary control for the vibration reduction of a flexible marine riser system in the presence of parametric uncertainties and system states obtained inaccurately. To this end, an adaptive output feedback boundary control is proposed to suppress the riser's vibration fusing with observer-based backstepping, high-gain observers and robust adaptive control theory. In addition, the parameter adaptive laws are designed to compensate for the system parametric uncertainties, and the disturbance observer is introduced to mitigate the effects of external environmental disturbance. The uniformly bounded stability of the closed-loop system is achieved through rigorous Lyapunov analysis without any discretisation or simplification of the dynamics in the time and space, and the state observer error is ensured to exponentially converge to zero as time grows to infinity. In the end, the simulation and comparison studies are carried out to illustrate the performance of the proposed control under the proper choice of the design parameters. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Camera Based Closed Loop Control for Partial Penetration Welding of Overlap Joints

NASA Astrophysics Data System (ADS)

Abt, F.; Heider, A.; Weber, R.; Graf, T.; Blug, A.; Carl, D.; Höfler, H.; Nicolosi, L.; Tetzlaff, R.

Welding of overlap joints with partial penetration in automotive applications is a challenging process, since the laser power must be set very precisely to achieve a proper connection between the two joining partners without damaging the backside of the sheet stack. Even minor changes in welding conditions can lead to bad results. To overcome this problem a camera based closed loop control for partial penetration welding of overlap joints was developed. With this closed loop control it is possible to weld such configurations with a stable process result even under changing welding conditions.

Closed loop models for analyzing the effects of simulator characteristics. [digital simulation of human operators

NASA Technical Reports Server (NTRS)

Baron, S.; Muralidharan, R.; Kleinman, D. L.

1978-01-01

The optimal control model of the human operator is used to develop closed loop models for analyzing the effects of (digital) simulator characteristics on predicted performance and/or workload. Two approaches are considered: the first utilizes a continuous approximation to the discrete simulation in conjunction with the standard optimal control model; the second involves a more exact discrete description of the simulator in a closed loop multirate simulation in which the optimal control model simulates the pilot. Both models predict that simulator characteristics can have significant effects on performance and workload.

Modern digital flight control system design for VTOL aircraft

NASA Technical Reports Server (NTRS)

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

1979-01-01

Methods for and results from the design and evaluation of a digital flight control system (DFCS) for a CH-47B helicopter are presented. The DFCS employed proportional-integral control logic to provide rapid, precise response to automatic or manual guidance commands while following conventional or spiral-descent approach paths. It contained altitude- and velocity-command modes, and it adapted to varying flight conditions through gain scheduling. Extensive use was made of linear systems analysis techniques. The DFCS was designed, using linear-optimal estimation and control theory, and the effects of gain scheduling are assessed by examination of closed-loop eigenvalues and time responses.

Bayesian nonparametric adaptive control using Gaussian processes.

PubMed

Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

2015-03-01

Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

Automatic control of finite element models for temperature-controlled radiofrequency ablation

PubMed Central

Haemmerich, Dieter; Webster, John G

2005-01-01

Background The finite element method (FEM) has been used to simulate cardiac and hepatic radiofrequency (RF) ablation. The FEM allows modeling of complex geometries that cannot be solved by analytical methods or finite difference models. In both hepatic and cardiac RF ablation a common control mode is temperature-controlled mode. Commercial FEM packages don't support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. Methods We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. Results We present results of a temperature controlled 3-D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100°C. The closed loop system simulation output closely correlated with the FEM model, and allowed us to optimize control parameters. Discussion The closed loop control of the FEM model allowed us to implement temperature controlled RF ablation with minimal user input. PMID:16018811

An efficient transmission power control scheme for temperature variation in wireless sensor networks.

PubMed

Lee, Jungwook; Chung, Kwangsue

2011-01-01

Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption.

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures.

PubMed

Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib

2018-05-10

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Model-based wavefront sensorless adaptive optics system for large aberrations and extended objects.

PubMed

Yang, Huizhen; Soloviev, Oleg; Verhaegen, Michel

2015-09-21

A model-based wavefront sensorless (WFSless) adaptive optics (AO) system with a 61-element deformable mirror is simulated to correct the imaging of a turbulence-degraded extended object. A fast closed-loop control algorithm, which is based on the linear relation between the mean square of the aberration gradients and the second moment of the image intensity distribution, is used to generate the control signals for the actuators of the deformable mirror (DM). The restoration capability and the convergence rate of the AO system are investigated with different turbulence strength wave-front aberrations. Simulation results show the model-based WFSless AO system can restore those images degraded by different turbulence strengths successfully and obtain the correction very close to the achievable capability of the given DM. Compared with the ideal correction of 61-element DM, the averaged relative error of RMS value is 6%. The convergence rate of AO system is independent of the turbulence strength and only depends on the number of actuators of DM.

Home Use of Day-and-Night Hybrid Closed-Loop Insulin Delivery in Suboptimally Controlled Adolescents With Type 1 Diabetes: A 3-Week, Free-Living, Randomized Crossover Trial.

PubMed

Tauschmann, Martin; Allen, Janet M; Wilinska, Malgorzata E; Thabit, Hood; Acerini, Carlo L; Dunger, David B; Hovorka, Roman

2016-11-01

This study evaluated the feasibility, safety, and efficacy of day-and-night hybrid closed-loop insulin delivery in adolescents with type 1 diabetes under free-living conditions. In an open-label randomized crossover study, 12 suboptimally controlled adolescents on insulin pump therapy (mean ± SD age 14.6 ± 3.1 years; HbA 1c 69 ± 8 mmol/mol [8.5 ± 0.7%]; duration of diabetes 7.8 ± 3.5 years) underwent two 21-day periods in which hybrid closed-loop insulin delivery was compared with sensor-augmented insulin pump therapy in random order. During the closed-loop intervention, a model predictive algorithm automatically directed insulin delivery between meals and overnight. Participants used a bolus calculator to administer prandial boluses. The proportion of time that sensor glucose was in the target range (3.9-10 mmol/L; primary end point) was increased during the closed-loop intervention compared with sensor-augmented insulin pump therapy by 18.8 ± 9.8 percentage points (mean ± SD; P < 0.001), the mean sensor glucose level was reduced by 1.8 ± 1.3 mmol/L (P = 0.001), and the time spent above target was reduced by 19.3 ± 11.3 percentage points (P < 0.001). The time spent with sensor glucose levels below 3.9 mmol/L was low and comparable between interventions (median difference 0.4 [interquartile range -2.2 to 1.3] percentage points; P = 0.33). Improved glucose control during closed-loop was associated with increased variability of basal insulin delivery (P < 0.001) and an increase in the total daily insulin dose (53.5 [39.5-72.1] vs. 51.5 [37.6-64.3] units/day; P = 0.006). Participants expressed positive attitudes and experience with the closed-loop system. Free-living home use of day-and-night closed-loop in suboptimally controlled adolescents with type 1 diabetes is safe, feasible, and improves glucose control without increasing the risk of hypoglycemia. Larger and longer studies are warranted. © 2016 by the American Diabetes Association.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

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.

Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat.

PubMed

Wu, Hemmings; Ghekiere, Hartwin; Beeckmans, Dorien; Tambuyzer, Tim; van Kuyck, Kris; Aerts, Jean-Marie; Nuttin, Bart

2015-04-21

Conventional deep brain stimulation (DBS) applies constant electrical stimulation to specific brain regions to treat neurological disorders. Closed-loop DBS with real-time feedback is gaining attention in recent years, after proved more effective than conventional DBS in terms of pathological symptom control clinically. Here we demonstrate the conceptualization and validation of a closed-loop DBS system using open-source hardware. We used hippocampal theta oscillations as system input, and electrical stimulation in the mesencephalic reticular formation (mRt) as controller output. It is well documented that hippocampal theta oscillations are highly related to locomotion, while electrical stimulation in the mRt induces freezing. We used an Arduino open-source microcontroller between input and output sources. This allowed us to use hippocampal local field potentials (LFPs) to steer electrical stimulation in the mRt. Our results showed that closed-loop DBS significantly suppressed locomotion compared to no stimulation, and required on average only 56% of the stimulation used in open-loop DBS to reach similar effects. The main advantages of open-source hardware include wide selection and availability, high customizability, and affordability. Our open-source closed-loop DBS system is effective, and warrants further research using open-source hardware for closed-loop neuromodulation.

Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat

PubMed Central

Wu, Hemmings; Ghekiere, Hartwin; Beeckmans, Dorien; Tambuyzer, Tim; van Kuyck, Kris; Aerts, Jean-Marie; Nuttin, Bart

2015-01-01

Conventional deep brain stimulation (DBS) applies constant electrical stimulation to specific brain regions to treat neurological disorders. Closed-loop DBS with real-time feedback is gaining attention in recent years, after proved more effective than conventional DBS in terms of pathological symptom control clinically. Here we demonstrate the conceptualization and validation of a closed-loop DBS system using open-source hardware. We used hippocampal theta oscillations as system input, and electrical stimulation in the mesencephalic reticular formation (mRt) as controller output. It is well documented that hippocampal theta oscillations are highly related to locomotion, while electrical stimulation in the mRt induces freezing. We used an Arduino open-source microcontroller between input and output sources. This allowed us to use hippocampal local field potentials (LFPs) to steer electrical stimulation in the mRt. Our results showed that closed-loop DBS significantly suppressed locomotion compared to no stimulation, and required on average only 56% of the stimulation used in open-loop DBS to reach similar effects. The main advantages of open-source hardware include wide selection and availability, high customizability, and affordability. Our open-source closed-loop DBS system is effective, and warrants further research using open-source hardware for closed-loop neuromodulation. PMID:25897892

Real-time control of hind limb functional electrical stimulation using feedback from dorsal root ganglia recordings

NASA Astrophysics Data System (ADS)

Bruns, Tim M.; Wagenaar, Joost B.; Bauman, Matthew J.; Gaunt, Robert A.; Weber, Douglas J.

2013-04-01

Objective. Functional electrical stimulation (FES) approaches often utilize an open-loop controller to drive state transitions. The addition of sensory feedback may allow for closed-loop control that can respond effectively to perturbations and muscle fatigue. Approach. We evaluated the use of natural sensory nerve signals obtained with penetrating microelectrode arrays in lumbar dorsal root ganglia (DRG) as real-time feedback for closed-loop control of FES-generated hind limb stepping in anesthetized cats. Main results. Leg position feedback was obtained in near real-time at 50 ms intervals by decoding the firing rates of more than 120 DRG neurons recorded simultaneously. Over 5 m of effective linear distance was traversed during closed-loop stepping trials in each of two cats. The controller compensated effectively for perturbations in the stepping path when DRG sensory feedback was provided. The presence of stimulation artifacts and the quality of DRG unit sorting did not significantly affect the accuracy of leg position feedback obtained from the linear decoding model as long as at least 20 DRG units were included in the model. Significance. This work demonstrates the feasibility and utility of closed-loop FES control based on natural neural sensors. Further work is needed to improve the controller and electrode technologies and to evaluate long-term viability.

Real-time control of hind limb functional electrical stimulation using feedback from dorsal root ganglia recordings

PubMed Central

Bruns, Tim M; Wagenaar, Joost B; Bauman, Matthew J; Gaunt, Robert A; Weber, Douglas J

2013-01-01

Objective Functional electrical stimulation (FES) approaches often utilize an open-loop controller to drive state transitions. The addition of sensory feedback may allow for closed-loop control that can respond effectively to perturbations and muscle fatigue. Approach We evaluated the use of natural sensory nerve signals obtained with penetrating microelectrode arrays in lumbar dorsal root ganglia (DRG) as real-time feedback for closed-loop control of FES-generated hind limb stepping in anesthetized cats. Main results Leg position feedback was obtained in near real-time at 50 ms intervals by decoding the firing rates of more than 120 DRG neurons recorded simultaneously. Over 5 m of effective linear distance was traversed during closed-loop stepping trials in each of two cats. The controller compensated effectively for perturbations in the stepping path when DRG sensory feedback was provided. The presence of stimulation artifacts and the quality of DRG unit sorting did not significantly affect the accuracy of leg position feedback obtained from the linear decoding model as long as at least 20 DRG units were included in the model. Significance This work demonstrates the feasibility and utility of closed-loop FES control based on natural neural sensors. Further work is needed to improve the controller and electrode technologies and to evaluate long-term viability. PMID:23503062

Adaptive iterative learning control of a class of nonlinear time-delay systems with unknown backlash-like hysteresis input and control direction.

PubMed

Wei, Jianming; Zhang, Youan; Sun, Meimei; Geng, Baoliang

2017-09-01

This paper presents an adaptive iterative learning control scheme for a class of nonlinear systems with unknown time-varying delays and control direction preceded by unknown nonlinear backlash-like hysteresis. Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control. For the controller design, integral Lyapunov function candidate is used, which avoids the possible singularity problem by introducing hyperbolic tangent funciton. After compensating for uncertainties with time-varying delays by combining appropriate Lyapunov-Krasovskii function with Young's inequality, an adaptive iterative learning control scheme is designed through neural approximation technique and Nussbaum function method. On the basis of the hyperbolic tangent function's characteristics, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Closed-Loop and Robust Control of Quantum Systems

PubMed Central

Wang, Lin-Cheng

2013-01-01

For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H ∞ control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention. PMID:23997680

Control of a flexible link by shaping the closed loop frequency response function through optimised feedback filters

NASA Astrophysics Data System (ADS)

Del Vescovo, D.; D'Ambrogio, W.

1995-01-01

A frequency domain method is presented to design a closed-loop control for vibration reduction flexible mechanisms. The procedure is developed on a single-link flexible arm, driven by one rotary degree of freedom servomotor, although the same technique may be applied to similar systems such as supports for aerospace antennae or solar panels. The method uses the structural frequency response functions (FRFs), thus avoiding system identification, that produces modeling uncertainties. Two closed-loops are implemented: the inner loop uses acceleration feedback with the aim of making the FRF similar to that of an equivalent rigid link; the outer loop feeds back displacements to achieve a fast positioning response and null steady state error. In both cases, the controller type is established a priori, while actual characteristics are defined by an optimisation procedure in which the relevant FRF is constrained into prescribed bounds and stability is taken into account.

Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

PubMed

Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

2015-01-01

Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

A closed-loop photon beam control study for the Advanced Light Source

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

Portmann, G.; Bengtsson, J.

1993-05-01

The third generation Advanced Light Source (ALS) will produce extremely bright photon beams using undulators and wigglers. In order to position the photon beams accurate to the micron level, a closed-loop feedback system is being developed. Using photon position monitors and dipole corrector magnets, a closed-loop system can automatically compensate for modeling uncertainties and exogenous disturbances. The following paper will present a dynamics model for the perturbations of the closed orbit of the electron beam in the ALS storage ring including the vacuum chamber magnetic field penetration effects. Using this reference model, two closed-loop feedback algorithms will be compared --more » a classical PI controller and a two degree-of-freedom approach. The two degree-of-freedom method provides superior disturbance rejection while maintaining the desired performance goals. Both methods will address the need to gain schedule the controller due to the time varying dynamics introduced by changing field strengths when scanning the insertion devices.« less

Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

NASA Astrophysics Data System (ADS)

Wang, Jun-Song; Wang, Mei-Li; Li, Xiao-Li; Ernst, Niebur

2015-03-01

Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model (NPM). We propose that a proportional-derivative (PD) type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473208, 61025019, and 91132722), ONR MURI N000141010278, and NIH grant R01EY016281.

FPGA-based real time controller for high order correction in EDIFISE

NASA Astrophysics Data System (ADS)

Rodríguez-Ramos, L. F.; Chulani, H.; Martín, Y.; Dorta, T.; Alonso, A.; Fuensalida, J. J.

2012-07-01

EDIFISE is a technology demonstrator instrument developed at the Institute of Astrophysics of the Canary Islands (IAC), intended to explore the feasibility of combining Adaptive Optics with attenuated optical fibers in order to obtain high spatial resolution spectra at the surroundings of a star, as an alternative to coronagraphy. A simplified version with only tip tilt correction has been tested at the OGS telescope in Observatorio del Teide (Canary islands, Spain) and a complete version is intended to be tested at the OGS and at the WHT telescope in Observatorio del Roque de los Muchachos, (Canary Islands, Spain). This paper describes the FPGA-based real time control of the High Order unit, responsible of the computation of the actuation values of a 97-actuactor deformable mirror (11x11) with the information provided by a configurable wavefront sensor of up to 16x16 subpupils at 500 Hz (128x128 pixels). The reconfigurable logic hardware will allow both zonal and modal control approaches, will full access to select which mode loops should be closed and with a number of utilities for influence matrix and open loop response measurements. The system has been designed in a modular way to allow for easy upgrade to faster frame rates (1500 Hz) and bigger wavefront sensors (240x240 pixels), accepting also several interfaces from the WFS and towards the mirror driver. The FPGA-based (Field Programmable Gate Array) real time controller provides bias and flat-fielding corrections, subpupil slopes to modal matrix computation for up to 97 modes, independent servo loop controllers for each mode with user control for independent loop opening or closing, mode to actuator matrix computation and non-common path aberration correction capability. It also provides full housekeeping control via UPD/IP for matrix reloading and full system data logging.

AQUILA Remotely Piloted Vehicle System Technology Demonstrator (RPV-STD) Program. Volume 2. System Evolution and Engineering Testing

DTIC Science & Technology

1979-04-01

crosshead of the piston assembly. Shock transients at this location cause demagnetization of the magnet . This is being alleviated by in- stallation of magnets ...substantial structure, such as bulk - heads with edge cape. Soond, the wire-out foam *or* for the wing could not be sufficiently precise to preven the used for...characterize the power potential, fuel consumption, weight, bulk , and adaptability to closed loop control of candidate carburetion systems to be employed with

Adaptive control method for core power control in TRIGA Mark II reactor

NASA Astrophysics Data System (ADS)

Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

2018-01-01

The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

Application of frequency domain handling qualities criteria to the longitudinal landing task

NASA Technical Reports Server (NTRS)

Sarrafian, S. K.; Powers, B. G.

1985-01-01

Three frequency-domain handling qualities criteria have been applied to the observed data to correlate the actual pilot ratings assigned to generic transport configurations with stability augmentation during the longitudinal landing task. The criteria are based on closed-loop techniques using pitch attitude, altitude rate at the pilot station, and altitude at the pilot station as dominating control parameters during this task. It is found that most promising results are obtained with altitude control performed by closing an inner loop on pitch attitude and closing an outer loop on altitude.

Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2008-01-01

Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

Inadequate interaction between open- and closed-loop postural control in phobic postural vertigo.

PubMed

Wuehr, M; Pradhan, C; Novozhilov, S; Krafczyk, S; Brandt, T; Jahn, K; Schniepp, R

2013-05-01

Phobic postural vertigo (PPV) is characterized by a subjective dizziness and postural imbalance. Changes in postural control strategy may cause the disturbed postural performance in PPV. A better understanding of the mechanisms behind this change in strategy is required to improve the diagnostic tools and therapeutic options for this prevalent disorder. Here we apply stabilogram diffusion analysis (SDA) to examine the characteristics and modes of interaction of open- and closed-loop processes that make up the postural control scheme in PPV. Twenty patients with PPV and 20 age-matched healthy controls were recorded on a stabilometer platform with eyes open and with eyes closed. Spatio-temporal changes of the center of pressure (CoP) displacement were analyzed by means of SDA and complementary CoP amplitude measures. (1) Open-loop control mechanisms in PPV were disturbed because of a higher diffusion activity (p < 0.001). (2) The interaction of open- and closed-loop processes was altered in that the sensory feedback threshold of the system was lowered (p = 0.010). These two changes were comparable to those observed in healthy subjects during more demanding balance conditions such as standing with eyes closed. These data indicate that subjective imbalance in PPV is associated with characteristic changes in the coordination of open- and closed-loop mechanisms of postural control. Patients with PPV use sensory feedback inadequately during undisturbed stance, and this impairs postural performance. These changes are compatible with higher levels of anti-gravity muscle activity and co-contraction during the conscious concentration on control of postural stability.

Closed loop control of penetration depth during CO₂ laser lap welding processes.

PubMed

Sibillano, Teresa; Rizzi, Domenico; Mezzapesa, Francesco P; Lugarà, Pietro Mario; Konuk, Ali Riza; Aarts, Ronald; Veld, Bert Huis In 't; Ancona, Antonio

2012-01-01

In this paper we describe a novel spectroscopic closed loop control system capable of stabilizing the penetration depth during laser welding processes by controlling the laser power. Our novel approach is to analyze the optical emission from the laser generated plasma plume above the keyhole, to calculate its electron temperature as a process-monitoring signal. Laser power has been controlled by using a quantitative relationship between the penetration depth and the plasma electron temperature. The sensor is able to correlate in real time the difference between the measured electron temperature and its reference value for the requested penetration depth. Accordingly the closed loop system adjusts the power, thus maintaining the penetration depth.

Closed Loop Control of Penetration Depth during CO2 Laser Lap Welding Processes

PubMed Central

Sibillano, Teresa; Rizzi, Domenico; Mezzapesa, Francesco P.; Lugarà, Pietro Mario; Konuk, Ali Riza; Aarts, Ronald; Veld, Bert Huis in 't; Ancona, Antonio

2012-01-01

In this paper we describe a novel spectroscopic closed loop control system capable of stabilizing the penetration depth during laser welding processes by controlling the laser power. Our novel approach is to analyze the optical emission from the laser generated plasma plume above the keyhole, to calculate its electron temperature as a process-monitoring signal. Laser power has been controlled by using a quantitative relationship between the penetration depth and the plasma electron temperature. The sensor is able to correlate in real time the difference between the measured electron temperature and its reference value for the requested penetration depth. Accordingly the closed loop system adjusts the power, thus maintaining the penetration depth. PMID:23112646

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

PubMed

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

2015-08-24

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

Lidar-based wake tracking for closed-loop wind farm control

NASA Astrophysics Data System (ADS)

Raach, Steffen; Schlipf, David; Cheng, Po Wen

2016-09-01

This work presents two advancements towards closed-loop wake redirecting of a wind turbine. First, a model-based estimation approach is presented which uses a nacelle-based lidar system facing downwind to obtain information about the wake. A reduced order wake model is described which is then used in the estimation to track the wake. The tracking is demonstrated with lidar measurement data from an offshore campaign and with simulated lidar data from a SOWFA simulation. Second, a controller for closed-loop wake steering is presented. It uses the wake tracking information to set the yaw actuator of the wind turbine to redirect the wake to a desired position. Altogether, this paper aims to present the concept of closed-loop wake redirecting and gives a possible solution to it.

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter.

PubMed

Zeghlache, Samir; Benslimane, Tarak; Bouguerra, Abderrahmen

2017-11-01

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter. The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller. Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluation of three automatic oxygen therapy control algorithms on ventilated low birth weight neonates.

PubMed

Morozoff, Edmund P; Smyth, John A

2009-01-01

Neonates with under developed lungs often require oxygen therapy. During the course of oxygen therapy, elevated levels of blood oxygenation, hyperoxemia, must be avoided or the risk of chronic lung disease or retinal damage is increased. Low levels of blood oxygen, hypoxemia, may lead to permanent brain tissue damage and, in some cases, mortality. A closed loop controller that automatically administers oxygen therapy using 3 algorithms - state machine, adaptive model, and proportional integral derivative (PID) - is applied to 7 ventilated low birth weight neonates and compared to manual oxygen therapy. All 3 automatic control algorithms demonstrated their ability to improve manual oxygen therapy by increasing periods of normoxemia and reducing the need for manual FiO(2) adjustments. Of the three control algorithms, the adaptive model showed the best performance with 0.25 manual adjustments per hour and 73% time spent within target +/- 3% SpO(2).

Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

PubMed

Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

2011-12-01

In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

Novel adaptive neural control design for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

NASA Astrophysics Data System (ADS)

Bu, Xiangwei; Wu, Xiaoyan; He, Guangjun; Huang, Jiaqi

2016-03-01

This paper investigates the design of a novel adaptive neural controller for the longitudinal dynamics of a flexible air-breathing hypersonic vehicle with control input constraints. To reduce the complexity of controller design, the vehicle dynamics is decomposed into the velocity subsystem and the altitude subsystem, respectively. For each subsystem, only one neural network is utilized to approach the lumped unknown function. By employing a minimal-learning parameter method to estimate the norm of ideal weight vectors rather than their elements, there are only two adaptive parameters required for neural approximation. Thus, the computational burden is lower than the ones derived from neural back-stepping schemes. Specially, to deal with the control input constraints, additional systems are exploited to compensate the actuators. Lyapunov synthesis proves that all the closed-loop signals involved are uniformly ultimately bounded. Finally, simulation results show that the adopted compensation scheme can tackle actuator constraint effectively and moreover velocity and altitude can stably track their reference trajectories even when the physical limitations on control inputs are in effect.

Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

PubMed

Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding

2017-08-29

This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.

Study on digital closed-loop system of silicon resonant micro-sensor

NASA Astrophysics Data System (ADS)

Xu, Yefeng; He, Mengke

2008-10-01

Designing a micro, high reliability weak signal extracting system is a critical problem need to be solved in the application of silicon resonant micro-sensor. The closed-loop testing system based on FPGA uses software to replace hardware circuit which dramatically decrease the system's mass and power consumption and make the system more compact, both correlation theory and frequency scanning scheme are used in extracting weak signal, the adaptive frequency scanning arithmetic ensures the system real-time. The error model was analyzed to show the solution to enhance the system's measurement precision. The experiment results show that the closed-loop testing system based on FPGA has the personality of low power consumption, high precision, high-speed, real-time etc, and also the system is suitable for different kinds of Silicon Resonant Micro-sensor.

A Novel Switching-Based Control Framework for Improved Task Performance in Teleoperation System With Asymmetric Time-Varying Delays.

PubMed

Zhai, Di-Hua; Xia, Yuanqing

2018-02-01

This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work, the developed method can simultaneously handle the unknown kinematics/dynamics, asymmetric varying time delays, and prescribed performance control in a unified framework. It is shown that the developed controller can guarantee the prescribed transient-state and steady-state synchronization performances between the master and slave robots, which is demonstrated by the simulation study.

High-resolution retinal imaging through open-loop adaptive optics

NASA Astrophysics Data System (ADS)

Li, Chao; Xia, Mingliang; Li, Dayu; Mu, Quanquan; Xuan, Li

2010-07-01

Using the liquid crystal spatial light modulator (LC-SLM) as the wavefront corrector, an open-loop adaptive optics (AO) system for fundus imaging in vivo is constructed. Compared with the LC-SLM closed-loop AO system, the light energy efficiency is increased by a factor of 2, which is helpful for the safety of fundus illumination in vivo. In our experiment, the subjective accommodation method is used to precorrect the defocus aberration, and three subjects with different myopia 0, -3, and -5 D are tested. Although the residual wavefront error after correction cannot to detected, the fundus images adequately demonstrate that the imaging system reaches the resolution of a single photoreceptor cell through the open-loop correction. Without dilating and cyclopleging the eye, the continuous imaging for 8 s is recorded for one of the subjects.

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

NASA Astrophysics Data System (ADS)

Chen, Jiaxi; Li, Junmin

2018-02-01

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T-S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Self-entrainment to optimal gaits of an underactuated biomimetic swimming robot using adaptive frequency oscillators.

PubMed

Alessi, Alessio; Accoto, Dino; Guglielmelli, Eugenio

2015-08-01

Underactuated compliant swimming robots are characterized by a simple mechanical structure, capable to mimic the body undulation of many fish species. One of the design issue for these robots is the generation and control of best performing swimming gaits. In this paper we propose a new controller, based on AFO oscillators, to address this issue. After analyzing the effects of the motion on the robot natural frequencies, we show that the closed loop system is able to generate self-sustained oscillations, at a characteristic frequency, while maximizing swimming velocity.

Analytical design and evaluation of an active control system for helicopter vibration reduction and gust response alleviation

NASA Technical Reports Server (NTRS)

Taylor, R. B.; Zwicke, P. E.; Gold, P.; Miao, W.

1980-01-01

An analytical study was conducted to define the basic configuration of an active control system for helicopter vibration and gust response alleviation. The study culminated in a control system design which has two separate systems: narrow band loop for vibration reduction and wider band loop for gust response alleviation. The narrow band vibration loop utilizes the standard swashplate control configuration to input controller for the vibration loop is based on adaptive optimal control theory and is designed to adapt to any flight condition including maneuvers and transients. The prime characteristics of the vibration control system is its real time capability. The gust alleviation control system studied consists of optimal sampled data feedback gains together with an optimal one-step-ahead prediction. The prediction permits the estimation of the gust disturbance which can then be used to minimize the gust effects on the helicopter.

Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

PubMed

Zhang, Qichao; Zhao, Dongbin; Wang, Ding

2018-01-01

In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Feasibility of outpatient fully integrated closed-loop control: first studies of wearable artificial pancreas.

PubMed

Kovatchev, Boris P; Renard, Eric; Cobelli, Claudio; Zisser, Howard C; Keith-Hynes, Patrick; Anderson, Stacey M; Brown, Sue A; Chernavvsky, Daniel R; Breton, Marc D; Farret, Anne; Pelletier, Marie-Josée; Place, Jérôme; Bruttomesso, Daniela; Del Favero, Simone; Visentin, Roberto; Filippi, Alessio; Scotton, Rachele; Avogaro, Angelo; Doyle, Francis J

2013-07-01

To evaluate the feasibility of a wearable artificial pancreas system, the Diabetes Assistant (DiAs), which uses a smart phone as a closed-loop control platform. Twenty patients with type 1 diabetes were enrolled at the Universities of Padova, Montpellier, and Virginia and at Sansum Diabetes Research Institute. Each trial continued for 42 h. The United States studies were conducted entirely in outpatient setting (e.g., hotel or guest house); studies in Italy and France were hybrid hospital-hotel admissions. A continuous glucose monitoring/pump system (Dexcom Seven Plus/Omnipod) was placed on the subject and was connected to DiAs. The patient operated the system via the DiAs user interface in open-loop mode (first 14 h of study), switching to closed-loop for the remaining 28 h. Study personnel monitored remotely via 3G or WiFi connection to DiAs and were available on site for assistance. The total duration of proper system communication functioning was 807.5 h (274 h in open-loop and 533.5 h in closed-loop), which represented 97.7% of the total possible time from admission to discharge. This exceeded the predetermined primary end point of 80% system functionality. This study demonstrated that a contemporary smart phone is capable of running outpatient closed-loop control and introduced a prototype system (DiAs) for further investigation. Following this proof of concept, future steps should include equipping insulin pumps and sensors with wireless capabilities, as well as studies focusing on control efficacy and patient-oriented clinical outcomes.

Development of acute tolerance to the EEG effect of propofol in rats.

PubMed

Ihmsen, H; Schywalsky, M; Tzabazis, A; Schwilden, H

2005-09-01

A previous study in rats with propofol suggested the development of acute tolerance to the EEG effect. The aim of this study was to evaluate acute tolerance by means of EEG-controlled closed-loop anaesthesia as this approach allows precise determination of drug requirement to maintain a defined drug effect. Ten male Sprague-Dawley rats [weight 402 (40) g, mean (SD)] were included in the study. The EEG was recorded with occipito-occipital needle electrodes and a modified median frequency (mMEF) of the EEG power spectrum was used as a pharmacodynamic control parameter. The propofol infusion rate was controlled by a model-based adaptive algorithm to maintain a set point of mMEF=3 (0.5) Hz for 90 min. The performance of the closed-loop system was characterized by the prediction error PE=(mMEF-set point)/set point. Plasma propofol concentrations were determined from arterial samples by HPLC. The chosen set point was successfully maintained in all rats. The median (SE) and absolute median values of PE were -5.0 (0.3) and 11.3 (0.2)% respectively. Propofol concentration increased significantly from 2.9 (2.2) microg ml(-1) at the beginning to 5.8 (3.8) microg ml(-1) at 90 min [mean (SD), P<0.05]. The cumulative dose increased linearly, with a mean infusion rate of 0.60 (0.16) mg kg(-1) min(-1). The minimum value of the mean arterial pressure during closed-loop administration of propofol was 130 (24) mm Hg, compared with a baseline value of 141 (12) mm Hg. The increase in propofol concentration at constant EEG effect indicates development of acute tolerance to the hypnotic effect of propofol.

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

2018-04-01

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Feasibility of overnight closed-loop control based on hourly blood glucose measurements.

PubMed

Patte, Caroline; Pleus, Stefan; Galley, Paul; Weinert, Stefan; Haug, Cornelia; Freckmann, Guido

2012-07-01

Safe and effective closed-loop control (artificial pancreas) is the ultimate goal of insulin delivery. In this study, we examined the performance of a closed-loop control algorithm used for the overnight time period to safely achieve a narrow target range of blood glucose (BG) concentrations prior to breakfast. The primary goal was to compare the quality of algorithm control during repeated overnight experiments. Twenty-three subjects with type 1 diabetes performed 2 overnight experiments on each of three visits at the study site, resulting in 138 overnight experiments. On the first evening, the subject's insulin therapy was applied; on the second, the insulin was delivered by an algorithm based on subcutaneous continuous glucose measurements (including meal control) until midnight. Overnight closed-loop control was applied between midnight and 6 a.m. based on hourly venous BG measurements during the first and second nights. The number of BG values within the target range (90-150 mg/dl) increased from 52.9% (219 out of 414 measurements) during the first nights to 72.2% (299 out of 414 measurements) during the second nights (p < .001, χ²-test). The occurrence of hypoglycemia interventions was reduced from 14 oral glucose interventions, the latest occurring at 2:36 a.m. during the first nights, to 1 intervention occurring at 1:02 a.m. during the second nights (p < .001, χ²-test). Overnight controller performance improved when optimized initial control was given; this was suggested by the better metabolic control during the second night. Adequate controller run-in time seems to be important for achieving good overnight control. In addition, the findings demonstrate that hourly BG data are sufficient for the closed-loop control algorithm tested to achieve appropriate glycemic control. © 2012 Diabetes Technology Society.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Design and simulation of a sensor for heliostat field closed loop control

NASA Astrophysics Data System (ADS)

Collins, Mike; Potter, Daniel; Burton, Alex

2017-06-01

Significant research has been completed in pursuit of capital cost reductions for heliostats [1],[2]. The camera array closed loop control concept has potential to radically alter the way heliostats are controlled and installed by replacing high quality open loop targeting systems with low quality targeting devices that rely on measurement of image position to remove tracking errors during operation. Although the system could be used for any heliostat size, the system significantly benefits small heliostats by reducing actuation costs, enabling large numbers of heliostats to be calibrated simultaneously, and enabling calibration of heliostats that produce low irradiance (similar or less than ambient light images) on Lambertian calibration targets, such as small heliostats that are far from the tower. A simulation method for the camera array has been designed and verified experimentally. The simulation tool demonstrates that closed loop calibration or control is possible using this device.

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

A dual-loop model of the human controller

NASA Technical Reports Server (NTRS)

Hess, R. A.

1977-01-01

A representative model of the human controller in single-axis compensatory tracking tasks that exhibits an internal feedback loop which is not evident in single-loop models now in common use is presented. This hypothetical inner-loop involves a neuromuscular command signal derived from the time rate of change of controlled element output which is due to control activity. It is not contended that the single-loop human controller models now in use are incorrect, but that they contain an implicit but important internal loop closure, which, if explicitly considered, can account for a good deal of the adaptive nature of the human controller in a systematic manner.

Pilot clinical application of an adaptive robotic system for young children with autism

PubMed Central

Bekele, Esubalew; Crittendon, Julie A; Swanson, Amy; Sarkar, Nilanjan; Warren, Zachary E

2013-01-01

It has been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders. This pilot feasibility study evaluated the application of a novel adaptive robot-mediated system capable of both administering and automatically adjusting joint attention prompts to a small group of preschool children with autism spectrum disorders (n = 6) and a control group (n = 6). Children in both groups spent more time looking at the humanoid robot and were able to achieve a high level of accuracy across trials. However, across groups, children required higher levels of prompting to successfully orient within robot-administered trials. The results highlight both the potential benefits of closed-loop adaptive robotic systems as well as current limitations of existing humanoid-robotic platforms. PMID:24104517

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

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

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

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

NASA Astrophysics Data System (ADS)

Roslund, Jonathan; Shir, Ofer M.; Bäck, Thomas; Rabitz, Herschel

2009-10-01

Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to ˜9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem’s Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape’s local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.

Construction of a 2- by 2-foot transonic adaptive-wall test section at the NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Morgan, Daniel G.; Lee, George

1986-01-01

The development of a new production-size, two-dimensional, adaptive-wall test section with ventilated walls at the NASA Ames Research Center is described. The new facility incorporates rapid closed-loop operation, computer/sensor integration, and on-line interference assessment and wall corrections. Air flow through the test section is controlled by a series of plenum compartments and three-way slide vales. A fast-scan laser velocimeter was built to measure velocity boundary conditions for the interference assessment scheme. A 15.2-cm- (6.0-in.-) chord NACA 0012 airfoil model will be used in the first experiments during calibration of the facility.

A comparative approach to closed-loop computation.

PubMed

Roth, E; Sponberg, S; Cowan, N J

2014-04-01

Neural computation is inescapably closed-loop: the nervous system processes sensory signals to shape motor output, and motor output consequently shapes sensory input. Technological advances have enabled neuroscientists to close, open, and alter feedback loops in a wide range of experimental preparations. The experimental capability of manipulating the topology-that is, how information can flow between subsystems-provides new opportunities to understand the mechanisms and computations underlying behavior. These experiments encompass a spectrum of approaches from fully open-loop, restrained preparations to the fully closed-loop character of free behavior. Control theory and system identification provide a clear computational framework for relating these experimental approaches. We describe recent progress and new directions for translating experiments at one level in this spectrum to predictions at another level. Operating across this spectrum can reveal new understanding of how low-level neural mechanisms relate to high-level function during closed-loop behavior. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessing performance of closed-loop insulin delivery systems by continuous glucose monitoring: drawbacks and way forward.

PubMed

Hovorka, Roman; Nodale, Marianna; Haidar, Ahmad; Wilinska, Malgorzata E

2013-01-01

We investigated whether continuous glucose monitoring (CGM) levels can accurately assess glycemic control while directing closed-loop insulin delivery. Data were analyzed retrospectively from 33 subjects with type 1 diabetes who underwent closed-loop and conventional pump therapy on two separate nights. Glycemic control was evaluated by reference plasma glucose and contrasted against three methods based on Navigator (Abbott Diabetes Care, Alameda, CA) CGM levels. Glucose mean and variability were estimated by unmodified CGM levels with acceptable clinical accuracy. Time when glucose was in target range was overestimated by CGM during closed-loop nights (CGM vs. plasma glucose median [interquartile range], 86% [65-97%] vs. 75% [59-91%]; P=0.04) but not during conventional pump therapy (57% [32-72%] vs. 51% [29-68%]; P=0.82) providing comparable treatment effect (mean [SD], 28% [29%] vs. 23% [21%]; P=0.11). Using the CGM measurement error of 15% derived from plasma glucose-CGM pairs (n=4,254), stochastic interpretation of CGM gave unbiased estimate of time in target during both closed-loop (79% [62-86%] vs. 75% [59-91%]; P=0.24) and conventional pump therapy (54% [33-66%] vs. 51% [29-68%]; P=0.44). Treatment effect (23% [24%] vs. 23% [21%]; P=0.96) and time below target were accurately estimated by stochastic CGM. Recalibrating CGM using reference plasma glucose values taken at the start and end of overnight closed-loop was not superior to stochastic CGM. CGM is acceptable to estimate glucose mean and variability, but without adjustment it may overestimate benefit of closed-loop. Stochastic CGM provided unbiased estimate of time when glucose is in target and below target and may be acceptable for assessment of closed-loop in the outpatient setting.

Does Mckuer's Law Hold for Heart Rate Control via Biofeedback Display?

NASA Technical Reports Server (NTRS)

Courter, B. J.; Jex, H. R.

1984-01-01

Some persons can control their pulse rate with the aid of a biofeedback display. If the biofeedback display is modified to show the error between a command pulse-rate and the measured rate, a compensatory (error correcting) heart rate tracking control loop can be created. The dynamic response characteristics of this control loop when subjected to step and quasi-random disturbances were measured. The control loop includes a beat-to-beat cardiotachmeter differenced with a forcing function from a quasi-random input generator; the resulting error pulse-rate is displayed as feedback. The subject acts to null the displayed pulse-rate error, thereby closing a compensatory control loop. McRuer's Law should hold for this case. A few subjects already skilled in voluntary pulse-rate control were tested for heart-rate control response. Control-law properties are derived, such as: crossover frequency, stability margins, and closed-loop bandwidth. These are evaluated for a range of forcing functions and for step as well as random disturbances.

Model-based adaptive sliding mode control of the subcritical boiler-turbine system with uncertainties.

PubMed

Tian, Zhen; Yuan, Jingqi; Xu, Liang; Zhang, Xiang; Wang, Jingcheng

2018-05-25

As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction. Copyright © 2018. Published by Elsevier Ltd.

Dual RBFNNs-Based Model-Free Adaptive Control With Aspen HYSYS Simulation.

PubMed

Zhu, Yuanming; Hou, Zhongsheng; Qian, Feng; Du, Wenli

2017-03-01

In this brief, we propose a new data-driven model-free adaptive control (MFAC) method with dual radial basis function neural networks (RBFNNs) for a class of discrete-time nonlinear systems. The main novelty lies in that it provides a systematic design method for controller structure by the direct usage of I/O data, rather than using the first-principle model or offline identified plant model. The controller structure is determined by equivalent-dynamic-linearization representation of the ideal nonlinear controller, and the controller parameters are tuned by the pseudogradient information extracted from the I/O data of the plant, which can deal with the unknown nonlinear system. The stability of the closed-loop control system and the stability of the training process for RBFNNs are guaranteed by rigorous theoretical analysis. Meanwhile, the effectiveness and the applicability of the proposed method are further demonstrated by the numerical example and Aspen HYSYS simulation of distillation column in crude styrene produce process.

Adaptive optics for the ESO-VLT

NASA Astrophysics Data System (ADS)

Merkle, Fritz

1989-04-01

This paper discusses adaptive optics, its performance, and its requirements for applications in astronomy to overcome limitations due to atmospheric turbulence. Guidelines for the implementation of these devices in telescopes are given, in particular for the Very Large Telescope (VLT) at ESO. It is intended to equip each one of the four 8-m telescopes of the VLT, which are arranged in a linear array with an independent adaptive optical system. These systems will serve the individual and the combined coude foci. A small-scale prototype adaptive system is under development. It is equipped with a 19-piezoelectric-actuator deformable mirror, a Shack-Hartmann-type wavefront sensor, and a dedicated wavefront computer for closing the feedback loop. This system is based on a polychromatic approach; i.e., it senses the wavefront in the visible, but the adaptive correction loop works at 3-5 microns.

A low power flash-FPGA based brain implant micro-system of PID control.

PubMed

Lijuan Xia; Fattah, Nabeel; Soltan, Ahmed; Jackson, Andrew; Chester, Graeme; Degenaar, Patrick

2017-07-01

In this paper, we demonstrate that a low power flash FPGA based micro-system can provide a low power programmable interface for closed-loop brain implant inter- faces. The proposed micro-system receives recording local field potential (LFP) signals from an implanted probe, performs closed-loop control using a first order control system, then converts the signal into an optogenetic control stimulus pattern. Stimulus can be implemented through optoelectronic probes. The long term target is for both fundamental neuroscience applications and for clinical use in treating epilepsy. Utilizing our device, closed-loop processing consumes only 14nJ of power per PID cycle compared to 1.52μJ per cycle for a micro-controller implementation. Compared to an application specific digital integrated circuit, flash FPGA's are inherently programmable.

Overnight closed-loop insulin delivery with model predictive control: assessment of hypoglycemia and hyperglycemia risk using simulation studies.

PubMed

Wilinska, Malgorzata E; Budiman, Erwin S; Taub, Marc B; Elleri, Daniela; Allen, Janet M; Acerini, Carlo L; Dunger, David B; Hovorka, Roman

2009-09-01

Hypoglycemia and hyperglycemia during closed-loop insulin delivery based on subcutaneous (SC) glucose sensing may arise due to (1) overdosing and underdosing of insulin by control algorithm and (2) difference between plasma glucose (PG) and sensor glucose, which may be transient (kinetics origin and sensor artifacts) or persistent (calibration error [CE]). Using in silico testing, we assessed hypoglycemia and hyperglycemia incidence during over-night closed loop. Additionally, a comparison was made against incidence observed experimentally during open-loop single-night in-clinic studies in young people with type 1 diabetes mellitus (T1DM) treated by continuous SC insulin infusion. Simulation environment comprising 18 virtual subjects with T1DM was used to simulate overnight closed-loop study with a model predictive control (MPC) algorithm. A 15 h experiment started at 17:00 and ended at 08:00 the next day. Closed loop commenced at 21:00 and continued for 11 h. At 18:00, protocol included meal (50 g carbohydrates) accompanied by prandial insulin. The MPC algorithm advised on insulin infusion every 15 min. Sensor glucose was obtained by combining model-calculated noise-free interstitial glucose with experimentally derived transient and persistent sensor artifacts associated with FreeStyle Navigator (FSN). Transient artifacts were obtained from FSN sensor pairs worn by 58 subjects with T1DM over 194 nighttime periods. Persistent difference due to FSN CE was quantified from 585 FSN sensor insertions, yielding 1421 calibration sessions from 248 subjects with diabetes. Episodes of severe (PG < or = 36 mg/dl) and significant (PG < or = 45 mg/dl) hypoglycemia and significant hyperglycemia (PG > or = 300 mg/dl) were extracted from 18,000 simulated closed-loop nights. Severe hypoglycemia was not observed when FSN CE was less than 45%. Hypoglycemia and hyperglycemia incidence during open loop was assessed from 21 overnight studies in 17 young subjects with T1DM (8 males; 13.5 +/- 3.6 years of age; body mass index 21.0 +/- 4.0 kg/m2; duration diabetes 6.4 +/- 4.1 years; hemoglobin A1c 8.5% +/- 1.8%; mean +/- standard deviation) participating in the Artificial Pancreas Project at Cambridge. Severe and significant hypoglycemia during simulated closed loop occurred 0.75 and 17.11 times per 100 person years compared to 1739 and 3479 times per 100 person years during experimental open loop, respectively. Significant hyperglycemia during closed loop and open loop occurred 75 and 15,654 times per 100 person years, respectively. The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during stimulated overnight closed loop with MPC compared to that observed during open-loop overnight clinical studies in young subjects with T1DM. Hyperglycemia was 200 times less likely. Overnight closed loop with the FSN and the MPC algorithm is expected to reduce substantially the risk of hypoglycemia and hyperglycemia. 2009 Diabetes Technology Society.

Closed-Loop Control System for Friction Stir Welding Retractable Pin Tool

NASA Technical Reports Server (NTRS)

Ding, R. Jeffrey; Romine, Peter L.; Munafo, Paul M. (Technical Monitor)

2001-01-01

NASA invention disclosure, NASA Case No. MFS-31413, entitled "System for Controlling the Stirring Pin of a Friction Stir Welding Apparatus", (Patent Pending) authored by Jeff Ding, Dr Peter Romine and Pete Oelgoetz, addresses the precision control of the friction stir welding process. The closed-loop control system automatically adjusts the spinning welding pin, real-time, to maintain a precise penetration ligament (i.e., distance between pin-tip and weld panel backside surface). A specific pin length can be maintained while welding constant thickness or tapered material thickness weld panels. The closed-loop control system provides operator data and information relative to the exact position of the welding pin inside the weld joint. This paper presents the closed-loop RPT control system that operates using the auto-feedback of force signals sensed by the tip and shoulder of the welding pin. Significance: The FSW process can be successfully used in a production environment only if there is a method or technique that informs the FSW operator the precise location of the welding pin inside the weld joint. This is essential for applications in aerospace, automotive, pressure vessel, commercial aircraft and other industries.

Adaptive Approximation-Based Regulation Control for a Class of Uncertain Nonlinear Systems Without Feedback Linearizability.

PubMed

Wang, Ning; Sun, Jing-Chao; Han, Min; Zheng, Zhongjiu; Er, Meng Joo

2017-09-06

In this paper, for a general class of uncertain nonlinear (cascade) systems, including unknown dynamics, which are not feedback linearizable and cannot be solved by existing approaches, an innovative adaptive approximation-based regulation control (AARC) scheme is developed. Within the framework of adding a power integrator (API), by deriving adaptive laws for output weights and prediction error compensation pertaining to single-hidden-layer feedforward network (SLFN) from the Lyapunov synthesis, a series of SLFN-based approximators are explicitly constructed to exactly dominate completely unknown dynamics. By the virtue of significant advancements on the API technique, an adaptive API methodology is eventually established in combination with SLFN-based adaptive approximators, and it contributes to a recursive mechanism for the AARC scheme. As a consequence, the output regulation error can asymptotically converge to the origin, and all other signals of the closed-loop system are uniformly ultimately bounded. Simulation studies and comprehensive comparisons with backstepping- and API-based approaches demonstrate that the proposed AARC scheme achieves remarkable performance and superiority in dealing with unknown dynamics.

First Results from a Hardware-in-the-Loop Demonstration of Closed-Loop Autonomous Formation Flying

NASA Technical Reports Server (NTRS)

Gill, E.; Naasz, Bo; Ebinuma, T.

2003-01-01

A closed-loop system for the demonstration of formation flying technologies has been developed at NASA s Goddard Space Flight Center. Making use of a GPS signal simulator with a dual radio frequency outlet, the system includes two GPS space receivers as well as a powerful onboard navigation processor dedicated to the GPS-based guidance, navigation, and control of a satellite formation in real-time. The closed-loop system allows realistic simulations of autonomous formation flying scenarios, enabling research in the fields of tracking and orbit control strategies for a wide range of applications. A sample scenario has been set up where the autonomous transition of a satellite formation from an initial along-track separation of 800 m to a final distance of 100 m has been demonstrated. As a result, a typical control accuracy of about 5 m has been achieved which proves the applicability of autonomous formation flying techniques to formations of satellites as close as 50 m.

Detailed ADM-based Modeling of Shock Retreat and X-ray Emission of τ Sco

NASA Astrophysics Data System (ADS)

Fletcher, C. L.; Petit, V.; Cohen, D. H.; Townsend, R. H.; Wade, G. A.

2018-01-01

Leveraging the improvement of spectropolarimeters over the past few decades, surveys have found that about 10% of OB-type stars host strong (˜ kG) and mostly dipolar surface magnetic fields. One B-type star, τ Sco, has a more complex surface magnetic field than the general population of OB stars. Interestingly, its X-ray luminosity is an order of magnitude higher than predicted from analytical models of magnetized winds. Previous studies of τ Sco's magnetosphere have predicted that the region of closed field loops should be located close to the stellar surface. However, the lack of X-ray variability and the location of the shock-heated plasma measured from forbidden-to-intercombination X-ray line ratios suggest that the hot plasma, and hence the closed magnetic loops, extend considerably farther from the stellar surface, implying a significantly lower mass loss rate than initially assumed. We present an adaptation of the Analytic Dynamical Magnetosphere model, describing the magnetic confinement of the stellar wind, for an arbitrary field loop configuration. This model is used to predict the shock-heated plasma temperatures for individual field loops, which are then compared to high resolution grating spectra from the Chandra X-ray Observatory. This comparison shows that larger closed magnetic loops are needed.

Gust alleviation - Criteria and control laws

NASA Technical Reports Server (NTRS)

Rynaski, E. G.

1979-01-01

The relationships between criteria specified for aircraft gust alleviation and the form of the control laws that result from the criteria are considered. Open-loop gust alleviation based on the linearized, small perturbation equations of aircraft motion is discussed, and an approximate solution of the open-loop control law is presented for the case in which the number of degrees of freedom of the aircraft exceeds the rank of the control effectiveness matrix. Excessive actuator lag is compensated for by taking into account actuator dynamics in the equations of motion, resulting in the specification of a general load network. Criteria for gust alleviation when output motions are gust alleviated and the closed-loop control law derived from them are examined and linear optimal control law is derived. Comparisons of the control laws reveal that the effectiveness of an open-loop control law is greatest at low aircraft frequencies but deteriorates as the natural frequency of the actuators is approached, while closed-loop methods are found to be more effective at higher frequencies.

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.

Simple robust control laws for robot manipulators. Part 1: Non-adaptive case

NASA Technical Reports Server (NTRS)

Wen, J. T.; Bayard, D. S.

1987-01-01

A new class of exponentially stabilizing control laws for joint level control of robot arms is introduced. It has been recently recognized that the nonlinear dynamics associated with robotic manipulators have certain inherent passivity properties. More specifically, the derivation of the robotic dynamic equations from the Hamilton's principle gives rise to natural Lyapunov functions for control design based on total energy considerations. Through a slight modification of the energy Lyapunov function and the use of a convenient lemma to handle third order terms in the Lyapunov function derivatives, closed loop exponential stability for both the set point and tracking control problem is demonstrated. The exponential convergence property also leads to robustness with respect to frictions, bounded modeling errors and instrument noise. In one new design, the nonlinear terms are decoupled from real-time measurements which completely removes the requirement for on-line computation of nonlinear terms in the controller implementation. In general, the new class of control laws offers alternatives to the more conventional computed torque method, providing tradeoffs between robustness, computation and convergence properties. Furthermore, these control laws have the unique feature that they can be adapted in a very simple fashion to achieve asymptotically stable adaptive control.

Fast autonomous holographic adaptive optics

NASA Astrophysics Data System (ADS)

Andersen, G.

2010-07-01

We have created a new adaptive optics system using a holographic modal wavefront sensing method capable of autonomous (computer-free) closed-loop control of a MEMS deformable mirror. A multiplexed hologram is recorded using the maximum and minimum actuator positions on the deformable mirror as the "modes". On reconstruction, an input beam will be diffracted into pairs of focal spots - the ratio of particular pairs determines the absolute wavefront phase at a particular actuator location. The wavefront measurement is made using a fast, sensitive photo-detector array such as a multi-pixel photon counters. This information is then used to directly control each actuator in the MEMS DM without the need for any computer in the loop. We present initial results of a 32-actuator prototype device. We further demonstrate that being an all-optical, parallel processing scheme, the speed is independent of the number of actuators. In fact, the limitations on speed are ultimately determined by the maximum driving speed of the DM actuators themselves. Finally, being modal in nature, the system is largely insensitive to both obscuration and scintillation. This should make it ideal for laser beam transmission or imaging under highly turbulent conditions.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

NASA Astrophysics Data System (ADS)

Yang, Xiong; Liu, Derong; Wang, Ding

2014-03-01

In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

Decentralized Sliding Mode Observer Based Dual Closed-Loop Fault Tolerant Control for Reconfigurable Manipulator against Actuator Failure.

PubMed

Zhao, Bo; Li, Chenghao; Liu, Derong; Li, Yuanchun

2015-01-01

This paper considers a decentralized fault tolerant control (DFTC) scheme for reconfigurable manipulators. With the appearance of norm-bounded failure, a dual closed-loop trajectory tracking control algorithm is proposed on the basis of the Lyapunov stability theory. Characterized by the modularization property, the actuator failure is estimated by the proposed decentralized sliding mode observer (DSMO). Moreover, the actuator failure can be treated in view of the local joint information, so its control performance degradation is independent of other normal joints. In addition, the presented DFTC scheme is significantly simplified in terms of the structure of the controller due to its dual closed-loop architecture, and its feasibility is highly reflected in the control of reconfigurable manipulators. Finally, the effectiveness of the proposed DFTC scheme is demonstrated using simulations.

Decentralized Sliding Mode Observer Based Dual Closed-Loop Fault Tolerant Control for Reconfigurable Manipulator against Actuator Failure

PubMed Central

Zhao, Bo; Li, Yuanchun

2015-01-01

This paper considers a decentralized fault tolerant control (DFTC) scheme for reconfigurable manipulators. With the appearance of norm-bounded failure, a dual closed-loop trajectory tracking control algorithm is proposed on the basis of the Lyapunov stability theory. Characterized by the modularization property, the actuator failure is estimated by the proposed decentralized sliding mode observer (DSMO). Moreover, the actuator failure can be treated in view of the local joint information, so its control performance degradation is independent of other normal joints. In addition, the presented DFTC scheme is significantly simplified in terms of the structure of the controller due to its dual closed-loop architecture, and its feasibility is highly reflected in the control of reconfigurable manipulators. Finally, the effectiveness of the proposed DFTC scheme is demonstrated using simulations. PMID:26181826

Optimal Micro-Scale Secondary Flow Control for the Management of High Cycle Fatigue and Distortion in Compact Inlet Diffusers

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Keller, Dennis J.

2002-01-01

The purpose of this study on micro-scale secondary flow control (MSFC) is to study the aerodynamic behavior of micro-vane effectors through their factor (i.e., the design variable) interactions and to demonstrate how these statistical interactions, when brought together in an optimal manner, determine design robustness. The term micro-scale indicates the vane effectors are small in comparison to the local boundary layer height. Robustness in this situation means that it is possible to design fixed MSFC robust installation (i.e.. open loop) which operates well over the range of mission variables and is only marginally different from adaptive (i.e., closed loop) installation design, which would require a control system. The inherent robustness of MSFC micro-vane effector installation designs comes about because of their natural aerodynamic characteristics and the manner in which these characteristics are brought together in an optimal manner through a structured Response Surface Methodology design process.

Closed-loop controller for chest compressions based on coronary perfusion pressure: a computer simulation study.

PubMed

Wang, Chunfei; Zhang, Guang; Wu, Taihu; Zhan, Ningbo; Wang, Yaling

2016-03-01

High-quality cardiopulmonary resuscitation contributes to cardiac arrest survival. The traditional chest compression (CC) standard, which neglects individual differences, uses unified standards for compression depth and compression rate in practice. In this study, an effective and personalized CC method for automatic mechanical compression devices is provided. We rebuild Charles F. Babbs' human circulation model with a coronary perfusion pressure (CPP) simulation module and propose a closed-loop controller based on a fuzzy control algorithm for CCs, which adjusts the CC depth according to the CPP. Compared with a traditional proportion-integration-differentiation (PID) controller, the performance of the fuzzy controller is evaluated in computer simulation studies. The simulation results demonstrate that the fuzzy closed-loop controller results in shorter regulation time, fewer oscillations and smaller overshoot than traditional PID controllers and outperforms the traditional PID controller for CPP regulation and maintenance.

Stabilization and analytical tuning rule of double-loop control scheme for unstable dead-time process

NASA Astrophysics Data System (ADS)

Ugon, B.; Nandong, J.; Zang, Z.

2017-06-01

The presence of unstable dead-time systems in process plants often leads to a daunting challenge in the design of standard PID controllers, which are not only intended to provide close-loop stability but also to give good performance-robustness overall. In this paper, we conduct stability analysis on a double-loop control scheme based on the Routh-Hurwitz stability criteria. We propose to use this unstable double-loop control scheme which employs two P/PID controllers to control first-order or second-order unstable dead-time processes typically found in process industries. Based on the Routh-Hurwitz stability necessary and sufficient criteria, we establish several stability regions which enclose within them the P/PID parameter values that guarantee close-loop stability of the double-loop control scheme. A systematic tuning rule is developed for the purpose of obtaining the optimal P/PID parameter values within the established regions. The effectiveness of the proposed tuning rule is demonstrated using several numerical examples and the result are compared with some well-established tuning methods reported in the literature.

A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.

PubMed

Wang, Ching-Fu; Yang, Shih-Hung; Lin, Sheng-Huang; Chen, Po-Chuan; Lo, Yu-Chun; Pan, Han-Chi; Lai, Hsin-Yi; Liao, Lun-De; Lin, Hui-Ching; Chen, Hsu-Yan; Huang, Wei-Chen; Huang, Wun-Jhu; Chen, You-Yin

Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller. Copyright © 2017 Elsevier Inc. All rights reserved.

Enabling Medical Device Interoperability for the Integrated Clinical Environment

DTIC Science & Technology

2016-02-01

Pajic M, Mangharam R, Sokolsky O, Arney D, Goldman JM, Lee I. Model-Driven Safety Analysis of Closed - Loop Medical Systems. IEEE Transactions on...Manigel J, Osborn D, Roellike T, Weininger S, Westenskow D, “Development of a Standard for Physiologic Closed Loop Controllers in Medical Devices...3 2010. 27. Arney D, Pajic M, Goldman JM, Lee I, Mangharam R, Sokolsky O, “Toward Patient Safety in Closed - Loop Medical Device Systems,” In

Adaptive optics system for Cassegrain focus of SUBARU 8.2-m telescope

NASA Astrophysics Data System (ADS)

Takami, Hideki; Takato, Naruhisa; Otsubo, Masashi; Kanzawa, Tomio; Kamata, Yukiko; Nakashima, Koji; Iye, Masanori

1998-09-01

The adaptive optics system for Subaru 8.2m telescope of the National Astronomical Observatory Japan has been developed for the Cassegrain ear-IR instruments, CIAO and IRCS. The system consists of a wavefront curvature sensor with 36 subaperture photon-counting avalanche photodiode modules and a bimorph deformable mirror with 36 electrodes. The expected Strehl ratio at K band exceeds 0.4 for objects that are located close enough to a bright guide star as faint as R equals 16 mag at the median seeing of 0.45 arcsec at Mauna Kea. The system will be in operation in 1999 as a natural guide star system, and will eventually be upgraded to a laser guide star system in cooperating an IR wavefront tilt sensor to provide nearly full sky. The construction of this common use system to Subaru telescope is now underway in our laboratory in Tokyo. Prior to starting the fabrication of this common use system, a full size prototype system was constructed and tested with the 1.6 m IR telescope at our observatory in Tokyo. This system has the identical optical design, deformable mirror, loop control computer to those for the Subaru system, while the wavefront sensing detectors were less-sensitive analog APDs. We succeeded in getting closed loop images of stars in K band with diffraction limited core. The Strehl ratio was around 0.5 and the factor of improvement was about 20 at K-band under the average seeing of 2 arcsec during the observation. The loop sped of the system was 2 K corrections per second.

Automated Droplet Manipulation Using Closed-Loop Axisymmetric Drop Shape Analysis.

PubMed

Yu, Kyle; Yang, Jinlong; Zuo, Yi Y

2016-05-17

Droplet manipulation plays an important role in a wide range of scientific and industrial applications, such as synthesis of thin-film materials, control of interfacial reactions, and operation of digital microfluidics. Compared to micron-sized droplets, which are commonly considered as spherical beads, millimeter-sized droplets are generally deformable by gravity, thus introducing nonlinearity into control of droplet properties. Such a nonlinear drop shape effect is especially crucial for droplet manipulation, even for small droplets, at the presence of surfactants. In this paper, we have developed a novel closed-loop axisymmetric drop shape analysis (ADSA), integrated into a constrained drop surfactometer (CDS), for manipulating millimeter-sized droplets. The closed-loop ADSA generalizes applications of the traditional drop shape analysis from a surface tension measurement methodology to a sophisticated tool for manipulating droplets in real time. We have demonstrated the feasibility and advantages of the closed-loop ADSA in three applications, including control of drop volume by automatically compensating natural evaporation, precise control of surface area variations for high-fidelity biophysical simulations of natural pulmonary surfactant, and steady control of surface pressure for in situ Langmuir-Blodgett transfer from droplets. All these applications have demonstrated the accuracy, versatility, applicability, and automation of this new ADSA-based droplet manipulation technique. Combining with CDS, the closed-loop ADSA holds great promise for advancing droplet manipulation in a variety of material and surface science applications, such as thin-film fabrication, self-assembly, and biophysical study of pulmonary surfactant.

Design and implementation of adaptive PI control schemes for web tension control in roll-to-roll (R2R) manufacturing.

PubMed

Raul, Pramod R; Pagilla, Prabhakar R

2015-05-01

In this paper, two adaptive Proportional-Integral (PI) control schemes are designed and discussed for control of web tension in Roll-to-Roll (R2R) manufacturing systems. R2R systems are used to transport continuous materials (called webs) on rollers from the unwind roll to the rewind roll. Maintaining web tension at the desired value is critical to many R2R processes such as printing, coating, lamination, etc. Existing fixed gain PI tension control schemes currently used in industrial practice require extensive tuning and do not provide the desired performance for changing operating conditions and material properties. The first adaptive PI scheme utilizes the model reference approach where the controller gains are estimated based on matching of the actual closed-loop tension control systems with an appropriately chosen reference model. The second adaptive PI scheme utilizes the indirect adaptive control approach together with relay feedback technique to automatically initialize the adaptive PI gains. These adaptive tension control schemes can be implemented on any R2R manufacturing system. The key features of the two adaptive schemes is that their designs are simple for practicing engineers, easy to implement in real-time, and automate the tuning process. Extensive experiments are conducted on a large experimental R2R machine which mimics many features of an industrial R2R machine. These experiments include trials with two different polymer webs and a variety of operating conditions. Implementation guidelines are provided for both adaptive schemes. Experimental results comparing the two adaptive schemes and a fixed gain PI tension control scheme used in industrial practice are provided and discussed. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Closed-Loop Neuromorphic Benchmarks

PubMed Central

Stewart, Terrence C.; DeWolf, Travis; Kleinhans, Ashley; Eliasmith, Chris

2015-01-01

Evaluating the effectiveness and performance of neuromorphic hardware is difficult. It is even more difficult when the task of interest is a closed-loop task; that is, a task where the output from the neuromorphic hardware affects some environment, which then in turn affects the hardware's future input. However, closed-loop situations are one of the primary potential uses of neuromorphic hardware. To address this, we present a methodology for generating closed-loop benchmarks that makes use of a hybrid of real physical embodiment and a type of “minimal” simulation. Minimal simulation has been shown to lead to robust real-world performance, while still maintaining the practical advantages of simulation, such as making it easy for the same benchmark to be used by many researchers. This method is flexible enough to allow researchers to explicitly modify the benchmarks to identify specific task domains where particular hardware excels. To demonstrate the method, we present a set of novel benchmarks that focus on motor control for an arbitrary system with unknown external forces. Using these benchmarks, we show that an error-driven learning rule can consistently improve motor control performance across a randomly generated family of closed-loop simulations, even when there are up to 15 interacting joints to be controlled. PMID:26696820

Closed-Loop Control and Advisory Mode Evaluation of an Artificial Pancreatic β Cell: Use of Proportional–Integral–Derivative Equivalent Model-Based Controllers

PubMed Central

Percival, Matthew W.; Zisser, Howard; Jovanovič, Lois; Doyle, Francis J.

2008-01-01

Background Using currently available technology, it is possible to apply modern control theory to produce a closed-loop artificial β cell. Novel use of established control techniques would improve glycemic control, thereby reducing the complications of diabetes. Two popular controller structures, proportional–integral–derivative (PID) and model predictive control (MPC), are compared first in a theoretical sense and then in two applications. Methods The Bergman model is transformed for use in a PID equivalent model-based controller. The internal model control (IMC) structure, which makes explicit use of the model, is compared with the PID controller structure in the transfer function domain. An MPC controller is then developed as an optimization problem with restrictions on its tuning parameters and is shown to be equivalent to an IMC controller. The controllers are tuned for equivalent performance and evaluated in a simulation study as a closed-loop controller and in an advisory mode scenario on retrospective clinical data. Results Theoretical development shows conditions under which PID and MPC controllers produce equivalent output via IMC. The simulation study showed that the single tuning parameter for the equivalent controllers relates directly to the closed-loop speed of response and robustness, an important result considering system uncertainty. The risk metric allowed easy identification of instances of inadequate control. Results of the advisory mode simulation showed that suitable tuning produces consistently appropriate delivery recommendations. Conclusion The conditions under which PID and MPC are equivalent have been derived. The MPC framework is more suitable given the extensions necessary for a fully closed-loop artificial β cell, such as consideration of controller constraints. Formulation of the control problem in risk space is attractive, as it explicitly addresses the asymmetry of the problem; this is done easily with MPC. PMID:19885240

Adaptive optics vision simulation and perceptual learning system based on a 35-element bimorph deformable mirror.

PubMed

Dai, Yun; Zhao, Lina; Xiao, Fei; Zhao, Haoxin; Bao, Hua; Zhou, Hong; Zhou, Yifeng; Zhang, Yudong

2015-02-10

An adaptive optics visual simulation combined with a perceptual learning (PL) system based on a 35-element bimorph deformable mirror (DM) was established. The larger stroke and smaller size of the bimorph DM made the system have larger aberration correction or superposition ability and be more compact. By simply modifying the control matrix or the reference matrix, select correction or superposition of aberrations was realized in real time similar to a conventional adaptive optics closed-loop correction. PL function was first integrated in addition to conventional adaptive optics visual simulation. PL training undertaken with high-order aberrations correction obviously improved the visual function of adult anisometropic amblyopia. The preliminary application of high-order aberrations correction with PL training on amblyopia treatment was being validated with a large scale population, which might have great potential in amblyopia treatment and visual performance maintenance.

L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.

PubMed

Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei

2011-06-01

In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2015-03-01

In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.

Extended state observer based robust adaptive control on SE(3) for coupled spacecraft tracking maneuver with actuator saturation and misalignment

NASA Astrophysics Data System (ADS)

Zhang, Jianqiao; Ye, Dong; Sun, Zhaowei; Liu, Chuang

2018-02-01

This paper presents a robust adaptive controller integrated with an extended state observer (ESO) to solve coupled spacecraft tracking maneuver in the presence of model uncertainties, external disturbances, actuator uncertainties including magnitude deviation and misalignment, and even actuator saturation. More specifically, employing the exponential coordinates on the Lie group SE(3) to describe configuration tracking errors, the coupled six-degrees-of-freedom (6-DOF) dynamics are developed for spacecraft relative motion, in which a generic fully actuated thruster distribution is considered and the lumped disturbances are reconstructed by using anti-windup technique. Then, a novel ESO, developed via second order sliding mode (SOSM) technique and adding linear correction terms to improve the performance, is designed firstly to estimate the disturbances in finite time. Based on the estimated information, an adaptive fast terminal sliding mode (AFTSM) controller is developed to guarantee the almost global asymptotic stability of the resulting closed-loop system such that the trajectory can be tracked with all the aforementioned drawbacks addressed simultaneously. Finally, the effectiveness of the controller is illustrated through numerical examples.

Adaptive control of turbulence intensity is accelerated by frugal flow sampling.

PubMed

Quinn, Daniel B; van Halder, Yous; Lentink, David

2017-11-01

The aerodynamic performance of vehicles and animals, as well as the productivity of turbines and energy harvesters, depends on the turbulence intensity of the incoming flow. Previous studies have pointed at the potential benefits of active closed-loop turbulence control. However, it is unclear what the minimal sensory and algorithmic requirements are for realizing this control. Here we show that very low-bandwidth anemometers record sufficient information for an adaptive control algorithm to converge quickly. Our online Newton-Raphson algorithm tunes the turbulence in a recirculating wind tunnel by taking readings from an anemometer in the test section. After starting at 9% turbulence intensity, the algorithm converges on values ranging from 10% to 45% in less than 12 iterations within 1% accuracy. By down-sampling our measurements, we show that very-low-bandwidth anemometers record sufficient information for convergence. Furthermore, down-sampling accelerates convergence by smoothing gradients in turbulence intensity. Our results explain why low-bandwidth anemometers in engineering and mechanoreceptors in biology may be sufficient for adaptive control of turbulence intensity. Finally, our analysis suggests that, if certain turbulent eddy sizes are more important to control than others, frugal adaptive control schemes can be particularly computationally effective for improving performance. © 2017 The Author(s).

Optimization of block-floating-point realizations for digital controllers with finite-word-length considerations.

PubMed

Wu, Jun; Hu, Xie-he; Chen, Sheng; Chu, Jian

2003-01-01

The closed-loop stability issue of finite-precision realizations was investigated for digital controllers implemented in block-floating-point format. The controller coefficient perturbation was analyzed resulting from using finite word length (FWL) block-floating-point representation scheme. A block-floating-point FWL closed-loop stability measure was derived which considers both the dynamic range and precision. To facilitate the design of optimal finite-precision controller realizations, a computationally tractable block-floating-point FWL closed-loop stability measure was then introduced and the method of computing the value of this measure for a given controller realization was developed. The optimal controller realization is defined as the solution that maximizes the corresponding measure, and a numerical optimization approach was adopted to solve the resulting optimal realization problem. A numerical example was used to illustrate the design procedure and to compare the optimal controller realization with the initial realization.

Advanced rotorcraft control using parameter optimization

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.

Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton.

PubMed

Grimm, Florian; Gharabaghi, Alireza

2016-01-01

Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement.

Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton

PubMed Central

Grimm, Florian; Gharabaghi, Alireza

2016-01-01

Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement. PMID:27445658

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

PubMed Central

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

2015-01-01

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

Stabilization of a system with saturating, non-monotone hysteresis and frequency dependent power losses by a PD controller

NASA Astrophysics Data System (ADS)

Ekanayake, D. B.; Iyer, R. V.

2015-02-01

We prove the closed loop stability of a PD controller for certain systems with saturating, non-monotone hysteresis and frequency dependent power losses. Most controllers use inverse compensators to cancel out actuator hysteresis nonlinearity. We show that we can achieve stability of the closed-loop system without an explicit inverse computation (using least squares minimization or otherwise).

In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes.

PubMed

Kovatchev, Boris P; Breton, Marc; Man, Chiara Dalla; Cobelli, Claudio

2009-01-01

Arguably, a minimally invasive system using subcutaneous (s.c.) continuous glucose monitoring (CGM) and s.c. insulin delivery via insulin pump would be a most feasible step to closed-loop control in type 1 diabetes mellitus (T1DM). Consequently, diabetes technology is focusing on developing an artificial pancreas using control algorithms to link CGM with s.c. insulin delivery. The future development of the artificial pancreas will be greatly accelerated by employing mathematical modeling and computer simulation. Realistic computer simulation is capable of providing invaluable information about the safety and the limitations of closed-loop control algorithms, guiding clinical studies, and out-ruling ineffective control scenarios in a cost-effective manner. Thus computer simulation testing of closed-loop control algorithms is regarded as a prerequisite to clinical trials of the artificial pancreas. In this paper, we present a system for in silico testing of control algorithms that has three principal components: (1) a large cohort of n=300 simulated "subjects" (n=100 adults, 100 adolescents, and 100 children) based on real individuals' data and spanning the observed variability of key metabolic parameters in the general population of people with T1DM; (2) a simulator of CGM sensor errors representative of Freestyle Navigator™, Guardian RT, or Dexcom™ STS™, 7-day sensor; and (3) a simulator of discrete s.c. insulin delivery via OmniPod Insulin Management System or Deltec Cozmo(®) insulin pump. The system has been shown to represent adequate glucose fluctuations in T1DM observed during meal challenges, and has been accepted by the Food and Drug Administration as a substitute to animal trials in the preclinical testing of closed-loop control strategies. © Diabetes Technology Society

An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction.

PubMed

Adams, Scott D; Kouzani, Abbas Z; Tye, Susannah J; Bennet, Kevin E; Berk, Michael

2018-02-13

Dynamic feedback based closed-loop medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. Closed-loop devices integrate a level of neurobiological feedback, which allows for real-time adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential feedback component in closed-loop therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson's disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of feedback for closed-loop neuromodulation treatments. A generic model of the closed-loop treatment is developed to describe the high-level functions of any system designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of closed-loop medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.

Robust Control Design via Linear Programming

NASA Technical Reports Server (NTRS)

Keel, L. H.; Bhattacharyya, S. P.

1998-01-01

This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.

Passivity-based control of linear time-invariant systems modelled by bond graph

NASA Astrophysics Data System (ADS)

Galindo, R.; Ngwompo, R. F.

2018-02-01

Closed-loop control systems are designed for linear time-invariant (LTI) controllable and observable systems modelled by bond graph (BG). Cascade and feedback interconnections of BG models are realised through active bonds with no loading effect. The use of active bonds may lead to non-conservation of energy and the overall system is modelled by proposed pseudo-junction structures. These structures are build by adding parasitic elements to the BG models and the overall system may become singularly perturbed. The structures for these interconnections can be seen as consisting of inner structures that satisfy energy conservation properties and outer structures including multiport-coupled dissipative fields. These fields highlight energy properties like passivity that are useful for control design. In both interconnections, junction structures and dissipative fields for the controllers are proposed, and passivity is guaranteed for the closed-loop systems assuring robust stability. The cascade interconnection is applied to the structural representation of closed-loop transfer functions, when a stabilising controller is applied to a given nominal plant. Applications are given when the plant and the controller are described by state-space realisations. The feedback interconnection is used getting necessary and sufficient stability conditions based on the closed-loop characteristic polynomial, solving a pole-placement problem and achieving zero-stationary state error.

Control of Systems With Slow Actuators Using Time Scale Separation

NASA Technical Reports Server (NTRS)

Stepanyan, Vehram; Nguyen, Nhan

2009-01-01

This paper addresses the problem of controlling a nonlinear plant with a slow actuator using singular perturbation method. For the known plant-actuator cascaded system the proposed scheme achieves tracking of a given reference model with considerably less control demand than would otherwise result when using conventional design techniques. This is the consequence of excluding the small parameter from the actuator dynamics via time scale separation. The resulting tracking error is within the order of this small parameter. For the unknown system the adaptive counterpart is developed based on the prediction model, which is driven towards the reference model by the control design. It is proven that the prediction model tracks the reference model with an error proportional to the small parameter, while the prediction error converges to zero. The resulting closed-loop system with all prediction models and adaptive laws remains stable. The benefits of the approach are demonstrated in simulation studies and compared to conventional control approaches.

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

PubMed

Peng, Zhouhua; Wang, Dan; Wang, Wei; Liu, Lu

2015-11-01

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control.

PubMed

Wang, Tong; Gao, Huijun; Qiu, Jianbin

2016-02-01

This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.

AQUILA Remotely Piloted Vehicle System Technology Demonstrator (RPV-STD) Program. Volume I. System Description and Capabilities

DTIC Science & Technology

1979-04-01

tools, simplification of equipment interfaces involved in manual operations to provide simple system preparation, closing flight control inner loops ...alti- tude, and heading rate. The closed loops operate in three primary modes: cruise, dead reckoning, and approach. The aircraft is stabilized by...onboard closed loops , so the operator is not required to maintain hands-on operation to keep it in the air. The operator is able to command airspeed

SCExAO: First Results and On-Sky Performance

NASA Astrophysics Data System (ADS)

Currie, Thayne; Guyon, Olivier; Martinache, Frantz; Clergeon, Christophe; McElwain, Michael; Thalmann, Christian; Jovanovic, Nemanja; Singh, Garima; Kudo, Tomoyuki

2014-01-01

We present new on-sky results for the Subaru Coronagraphic Extreme Adaptive Optics imager (SCExAO) verifying and quantifying the contrast gain enabled by key components: the closed-loop coronagraphic low-order wavefront sensor (CLOWFS) and focal plane wavefront control (``speckle nulling''). SCExAO will soon be coupled with a high-order, Pyramid wavefront sensor which will yield > 90% Strehl ratio and enable 106-107 contrast at small angular separations allowing us to image gas giant planets at solar system scales. Upcoming instruments like VAMPIRES, FIRST, and CHARIS will expand SCExAO's science capabilities.

The influence of a prediction display on the quasi-linear describing function and remnant measured with an adaptive analog-pilot in a closed loop

NASA Technical Reports Server (NTRS)

Dey, D.

1972-01-01

The effect of a prediction display on the human transfer characteristics is explained with the aid of a quasi-linear model. The prediction display causes an increase of the gain factor and the lead factor, a diminishing of the lag factor and a decrease of the remnant. Altogether, these factors yield a smaller mean square value of the control deviation and a simultaneous decrease of the mean square value of the stick signal.

Ascent Guidance for a Winged Boost Vehicle. M.S. Thesis

NASA Technical Reports Server (NTRS)

Corvin, Michael Alexander

1988-01-01

The objective of the advanced ascent guidance study was to investigate guidance concepts which could contribute to increased autonomy during ascent operations in a winged boost vehicle such as the proposed Shuttle II. The guidance scheme was required to yield near a full-optimal ascent in the presence of vehicle system and environmental dispersions. The study included consideration of trajectory shaping issues, trajectory design, closed loop and predictive adaptive guidance techniques and control of dynamic pressure by throttling. An extensive ascent vehicle simulation capability was developed for use in the study.

An error criterion for determining sampling rates in closed-loop control systems

NASA Technical Reports Server (NTRS)

Brecher, S. M.

1972-01-01

The determination of an error criterion which will give a sampling rate for adequate performance of linear, time-invariant closed-loop, discrete-data control systems was studied. The proper modelling of the closed-loop control system for characterization of the error behavior, and the determination of an absolute error definition for performance of the two commonly used holding devices are discussed. The definition of an adequate relative error criterion as a function of the sampling rate and the parameters characterizing the system is established along with the determination of sampling rates. The validity of the expressions for the sampling interval was confirmed by computer simulations. Their application solves the problem of making a first choice in the selection of sampling rates.

Design of dissipative low-authority controllers using an eigensystem assignment technique

NASA Technical Reports Server (NTRS)

Maghami, P. G.; Gupta, S.; Joshi, S. M.

1992-01-01

A novel method for the design of dissipative, low-authority controllers has been developed. The method uses a sequential approach along with eigensystem assignment to compute rate and position gain matrices that assign a number of closed-loop poles of the system to desired locations. Because the feedback gain matrices are symmetric and nonnegative definite, the closed-loop stability is always guaranteed regardless of the model order or parameter inaccuracies. The resulting (nominal) closed-loop system can have specified damping ratios for m modes, which makes the plant amenable to high-authority controller design, using methods such as LQG/LTR or H-infinity. A numerical example is worked out for a flexible structure in order to demonstrate the proposed technique.

Closed loop engine control for regulating NOx emissions, using a two-dimensional fuel-air curve

DOEpatents

Bourn, Gary D.; Smith, Jack A.; Gingrich, Jess W.

2007-01-30

An engine control strategy that ensures that NOx emissions from the engine will be maintained at an acceptable level. The control strategy is based on a two-dimensional fuel-air curve, in which air manifold pressure (AMP) is a function of fuel header pressure and engine speed. The control strategy provides for closed loop NOx adjustment to a base AMP value derived from the fuel-air curve.

Reliable numerical computation in an optimal output-feedback design

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm is presented for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters. The algorithm is a part of a design algorithm for optimal linear dynamic output-feedback controller that minimizes a finite-time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control-law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed-loop eigensystem. This approach through the use of an accurate Pade series approximation does not require the closed-loop system matrix to be diagonalizable. The algorithm was included in a control design package for optimal robust low-order controllers. Usefulness of the proposed numerical algorithm was demonstrated using numerous practical design cases where degeneracies occur frequently in the closed-loop system under an arbitrary controller design initialization and during the numerical search.

Prediction-based sampled-data H∞ controller design for attitude stabilisation of a rigid spacecraft with disturbances

NASA Astrophysics Data System (ADS)

Zhu, Baolong; Zhang, Zhiping; Zhou, Ding; Ma, Jie; Li, Shunli

2017-08-01

This paper investigates the H∞ control problem of the attitude stabilisation of a rigid spacecraft with external disturbances using prediction-based sampled-data control strategy. Aiming to achieve a 'virtual' closed-loop system, a type of parameterised sampled-data controller is designed by introducing a prediction mechanism. The resultant closed-loop system is equivalent to a hybrid system featured by a continuous-time and an impulsive differential system. By using a time-varying Lyapunov functional, a generalised bounded real lemma (GBRL) is first established for a kind of impulsive differential system. Based on this GBRL and Lyapunov functional approach, a sufficient condition is derived to guarantee the closed-loop system to be asymptotically stable and to achieve a prescribed H∞ performance. In addition, the controller parameter tuning is cast into a convex optimisation problem. Simulation and comparative results are provided to illustrate the effectiveness of the developed control scheme.

Application of ANFIS to Phase Estimation for Multiple Phase Shift Keying

NASA Technical Reports Server (NTRS)

Drake, Jeffrey T.; Prasad, Nadipuram R.

2000-01-01

The paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for estimating phase in Multiple Phase Shift Keying (M-PSK) modulation. A brief overview of communications phase estimation is provided. The modeling of both general open-loop, and closed-loop phase estimation schemes for M-PSK symbols with unknown structure are discussed. Preliminary performance results from simulation of the above schemes are presented.

Pilot clinical application of an adaptive robotic system for young children with autism.

PubMed

Bekele, Esubalew; Crittendon, Julie A; Swanson, Amy; Sarkar, Nilanjan; Warren, Zachary E

2014-07-01

It has been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders. This pilot feasibility study evaluated the application of a novel adaptive robot-mediated system capable of both administering and automatically adjusting joint attention prompts to a small group of preschool children with autism spectrum disorders (n = 6) and a control group (n = 6). Children in both groups spent more time looking at the humanoid robot and were able to achieve a high level of accuracy across trials. However, across groups, children required higher levels of prompting to successfully orient within robot-administered trials. The results highlight both the potential benefits of closed-loop adaptive robotic systems as well as current limitations of existing humanoid-robotic platforms. © The Author(s) 2013.

Non-common path aberration correction in an adaptive optics scanning ophthalmoscope.

PubMed

Sulai, Yusufu N; Dubra, Alfredo

2014-09-01

The correction of non-common path aberrations (NCPAs) between the imaging and wavefront sensing channel in a confocal scanning adaptive optics ophthalmoscope is demonstrated. NCPA correction is achieved by maximizing an image sharpness metric while the confocal detection aperture is temporarily removed, effectively minimizing the monochromatic aberrations in the illumination path of the imaging channel. Comparison of NCPA estimated using zonal and modal orthogonal wavefront corrector bases provided wavefronts that differ by ~λ/20 in root-mean-squared (~λ/30 standard deviation). Sequential insertion of a cylindrical lens in the illumination and light collection paths of the imaging channel was used to compare image resolution after changing the wavefront correction to maximize image sharpness and intensity metrics. Finally, the NCPA correction was incorporated into the closed-loop adaptive optics control by biasing the wavefront sensor signals without reducing its bandwidth.

Closed-Loop Aeromaneuvering for a Mars Precision Landing

NASA Technical Reports Server (NTRS)

Smith, Roy; Boussalis, Dhemetrios; Hadaegh, Fred Y.

1997-01-01

Controlled aeromaneuvering is considered as a means of achieving a precisely targeted landing on Mars. This paper presents a preliminary study of the control issues. The candidate vehicle is the existing Mars Pathfinder augmented with roll thrusters and a center of mass offset actuator. These allow control of both bank angle and lift force, giving the ability to control the range and cross-track during the aeromaneuvering entry. A preliminary control system structure is proposed and a design simulation illustrates significant targeting improvement under closed-loop control.

ZAG-Otolith: Modification of Otolith-Ocular Reflexes, Motion Perception and Manual Control during Variable Radius Centrifugation Following Space Flight

NASA Technical Reports Server (NTRS)

Wood, S. J.; Clarke, A. H.; Rupert, A. H.; Harm, D. L.; Clement, G. R.

2009-01-01

Two joint ESA-NASA studies are examining changes in otolith-ocular reflexes and motion perception following short duration space flights, and the operational implications of post-flight tilt-translation ambiguity for manual control performance. Vibrotactile feedback of tilt orientation is also being evaluated as a countermeasure to improve performance during a closed-loop nulling task. METHODS. Data is currently being collected on astronaut subjects during 3 preflight sessions and during the first 8 days after Shuttle landings. Variable radius centrifugation is utilized to elicit otolith reflexes in the lateral plane without concordant roll canal cues. Unilateral centrifugation (400 deg/s, 3.5 cm radius) stimulates one otolith positioned off-axis while the opposite side is centered over the axis of rotation. During this paradigm, roll-tilt perception is measured using a subjective visual vertical task and ocular counter-rolling is obtained using binocular video-oculography. During a second paradigm (216 deg/s, <20 cm radius), the effects of stimulus frequency (0.15 - 0.6 Hz) are examined on eye movements and motion perception. A closed-loop nulling task is also performed with and without vibrotactile display feedback of chair radial position. PRELIMINARY RESULTS. Data collection is currently ongoing. Results to date suggest there is a trend for perceived tilt and translation amplitudes to be increased at the low and medium frequencies on landing day compared to pre-flight. Manual control performance is improved with vibrotactile feedback. DISCUSSION. One result of this study will be to characterize the variability (gain, asymmetry) in both otolithocular responses and motion perception during variable radius centrifugation, and measure the time course of postflight recovery. This study will also address how adaptive changes in otolith-mediated reflexes correspond to one's ability to perform closed-loop nulling tasks following G-transitions, and whether manual control performance can be improved with vibrotactile feedback of orientation.

Modification of Otolith-Ocular Reflexes, Motion Perception and Manual Control During Variable Radius Centrifugation Following Space Flight

NASA Technical Reports Server (NTRS)

Wood, Scott J.; Clarke, A. H.; Rupert, A. H.; Harm, D. L.; Clement, G. R.

2009-01-01

Two joint ESA-NASA studies are examining changes in otolith-ocular reflexes and motion perception following short duration space flights, and the operational implications of post-flight tilt-translation ambiguity for manual control performance. Vibrotactile feedback of tilt orientation is also being evaluated as a countermeasure to improve performance during a closed-loop nulling task. Data is currently being collected on astronaut subjects during 3 preflight sessions and during the first 8 days after Shuttle landings. Variable radius centrifugation is utilized to elicit otolith reflexes in the lateral plane without concordant roll canal cues. Unilateral centrifugation (400 deg/s, 3.5 cm radius) stimulates one otolith positioned off-axis while the opposite side is centered over the axis of rotation. During this paradigm, roll-tilt perception is measured using a subjective visual vertical task and ocular counter-rolling is obtained using binocular video-oculography. During a second paradigm (216 deg/s, less than 20 cm radius), the effects of stimulus frequency (0.15 - 0.6 Hz) are examined on eye movements and motion perception. A closed-loop nulling task is also performed with and without vibrotactile display feedback of chair radial position. Data collection is currently ongoing. Results to date suggest there is a trend for perceived tilt and translation amplitudes to be increased at the low and medium frequencies on landing day compared to pre-flight. Manual control performance is improved with vibrotactile feedback. One result of this study will be to characterize the variability (gain, asymmetry) in both otolith-ocular responses and motion perception during variable radius centrifugation, and measure the time course of post-flight recovery. This study will also address how adaptive changes in otolith-mediated reflexes correspond to one's ability to perform closed-loop nulling tasks following G-transitions, and whether manual control performance can be improved with vibrotactile feedback of orientation.

Dynamic simulation of perturbation responses in a closed-loop virtual arm model.

PubMed

Du, Yu-Fan; He, Xin; Lan, Ning

2010-01-01

A closed-loop virtual arm (VA) model has been developed in SIMULINK environment by adding spinal reflex circuits and propriospinal neural networks to the open-loop VA model developed in early study [1]. An improved virtual muscle model (VM4.0) is used to speed up simulation and to generate more precise recruitment of muscle force at low levels of muscle activation. Time delays in the reflex loops are determined by their synaptic connections and afferent transmission back to the spinal cord. Reflex gains are properly selected so that closed-loop responses are stable. With the closed-loop VA model, we are developing an approach to evaluate system behaviors by dynamic simulation of perturbation responses. Joint stiffness is calculated based on simulated perturbation responses by a least-squares algorithm in MATLAB. This method of dynamic simulation will be essential for further evaluation of feedforward and reflex control of arm movement and position.

A novel system for automated propofol sedation: hybrid sedation system (HSS).

PubMed

Zaouter, Cedrick; Taddei, Riccardo; Wehbe, Mohamad; Arbeid, Erik; Cyr, Shantale; Giunta, Francesco; Hemmerling, Thomas M

2017-04-01

Closed-loop systems for propofol have been demonstrated to be safe and reliable for general anesthesia. However, no study has been conducted using a closed-loop system specifically designed for sedation in patients under spinal anesthesia. We developed an automatic anesthesia sedation system that allows for closed-loop delivery of propofol for sedation integrating a decision support system, called the hybrid sedation system (HSS). The objective of this study is to compare this system with standard practice. One hundred fifty patients were enrolled and randomly assigned to two groups: HSS-Group (N = 75), in which propofol was administered using a closed-loop system; Control Group (N = 75), in which propofol was delivered manually. The clinical performance of the propofol sedation control is defined as efficacy to maintain bispectral index (BIS) near 65. The clinical control was called 'Excellent', 'Good', 'Poor' and 'Inadequate' with BIS values within 10 %, from 11 to 20 %, 21 to 30 %, or greater than 30 % of the BIS target of 65, respectively. The controller performance was evaluated using Varvel's parameters. Data are presented as mean ± standard deviation, groups were compared using t test or Chi square test, P < 0.05. Clinical performance of sedation showed 'Excellent' control in the HSS-group for a significantly longer period of time (49 vs. 26 % in the control group, P < 0.0001). 'Poor' and 'Inadequate' sedation was significantly shorter in the HSS Group compared to the Control Group (11 and 10 % vs. 20 and 18 %, respectively, P < 0.0001). The novel, closed-loop system for propofol sedation showed better maintenance of the target BIS value compared to manual administration.

Probing the closed-loop model of mRNA translation in living cells

PubMed Central

Archer, Stuart K; Shirokikh, Nikolay E; Hallwirth, Claus V; Beilharz, Traude H; Preiss, Thomas

2015-01-01

The mRNA closed-loop, formed through interactions between the cap structure, poly(A) tail, eIF4E, eIF4G and PAB, features centrally in models of eukaryotic translation initiation, although direct support for its existence in vivo is not well established. Here, we investigated the closed-loop using a combination of mRNP isolation from rapidly cross-linked cells and high-throughput qPCR. Using the interaction between these factors and the opposing ends of mRNAs as a proxy for the closed-loop, we provide evidence that it is prevalent for eIF4E/4G-bound but unexpectedly sparse for PAB1-bound mRNAs, suggesting it primarily occurs during a distinct phase of polysome assembly. We observed mRNA-specific variation in the extent of closed-loop formation, consistent with a role for polysome topology in the control of gene expression. PMID:25826658

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

NASA Astrophysics Data System (ADS)

Bolus, M. F.; Willats, A. A.; Whitmire, C. J.; Rozell, C. J.; Stanley, G. B.

2018-04-01

Objective. Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. Approach. Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. Main results. The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. Significance. Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.

Test Platform for Advanced Digital Control of Brushless DC Motors (MSFC Center Director's Discretionary Fund)

NASA Technical Reports Server (NTRS)

Gwaltney, D. A.

2002-01-01

A FY 2001 Center Director's Discretionary Fund task to develop a test platform for the development, implementation. and evaluation of adaptive and other advanced control techniques for brushless DC (BLDC) motor-driven mechanisms is described. Important applications for BLDC motor-driven mechanisms are the translation of specimens in microgravity experiments and electromechanical actuation of nozzle and fuel valves in propulsion systems. Motor-driven aerocontrol surfaces are also being utilized in developmental X vehicles. The experimental test platform employs a linear translation stage that is mounted vertically and driven by a BLDC motor. Control approaches are implemented on a digital signal processor-based controller for real-time, closed-loop control of the stage carriage position. The goal of the effort is to explore the application of advanced control approaches that can enhance the performance of a motor-driven actuator over the performance obtained using linear control approaches with fixed gains. Adaptive controllers utilizing an exact model knowledge controller and a self-tuning controller are implemented and the control system performance is illustrated through the presentation of experimental results.

Design and Control of a Closed-Loop Brushless Torque Activator

DTIC Science & Technology

1990-05-01

AD-A270 760 Technical Report 1244 Design and Control of a Closed-Loop Brushless Torque Activator Michael Dean Levi MIT Artificial Intelligence... Brushless N00014-86-K-0685 Torque Actuator 6. AUTHOR(S) Michael Dean Levin 7. PERFORMING ORGANIZATION NAME(S) AND ADORESS(ES) B. PERFORMING...200 words) This’report explores the design and control issues associated with a brushless actuator capable of achieving extremely high torque

A Demonstration of a Versatile Low-order Wavefront Sensor Tested on Multiple Coronographs

NASA Astrophysics Data System (ADS)

Singh, Garima; Lozi, Julien; Jovanovic, Nemanja; Guyon, Olivier; Baudoz, Pierre; Martinache, Frantz; Kudo, Tomoyuki

2017-09-01

Detecting faint companions in close proximity to stars is one of the major goals of current/planned ground- and space-based high-contrast imaging instruments. High-performance coronagraphs can suppress the diffraction features and gain access to companions at small angular separation. However, the uncontrolled pointing errors degrade the coronagraphic performance by leaking starlight around the coronagraphic focal-plane mask, preventing the detection of companions at small separations. A Lyot-stop low-order wavefront sensor (LLOWFS) was therefore introduced to calibrate and measure these aberrations for focal-plane phase mask coronagraphs. This sensor quantifies the variations in wavefront error decomposed into a few Zernike modes by reimaging the diffracted starlight rejected by a reflective Lyot stop. The technique was tested with several coronagraphs on the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system at the Subaru Telescope. The wavefront was decomposed into 15 and 35 Zernike modes with an occulting and focal-plane phase mask coronagraph, respectively, which were used to drive a closed-loop correction in the laboratory. Using a 2000-actuator deformable mirror, a closed-loop pointing stability between 10-3-10-4 λ/D was achieved in the laboratory in H-band, with sub nanometer residuals for the other Zernike modes (Noll index > 4). On-sky, the low-order control of 10+ Zernike modes for the phase-induced amplitude apodization and the vector vortex coronagraphs was demonstrated, with a closed-loop pointing stability of {10}-4λ /D under good seeing and {10}-3λ /D under moderate seeing conditions readily achievable.

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

PubMed Central

Shirvalkar, Prasad; Veuthey, Tess L.; Dawes, Heather E.; Chang, Edward F.

2018-01-01

Pain is a subjective experience that alerts an individual to actual or potential tissue damage. Through mechanisms that are still unclear, normal physiological pain can lose its adaptive value and evolve into pathological chronic neuropathic pain. Chronic pain is a multifaceted experience that can be understood in terms of somatosensory, affective, and cognitive dimensions, each with associated symptoms and neural signals. While there have been many attempts to treat chronic pain, in this article we will argue that feedback-controlled ‘closed-loop’ deep brain stimulation (DBS) offers an urgent and promising route for treatment. Contemporary DBS trials for chronic pain use “open-loop” approaches in which tonic stimulation is delivered with fixed parameters to a single brain region. The impact of key variables such as the target brain region and the stimulation waveform is unclear, and long-term efficacy has mixed results. We hypothesize that chronic pain is due to abnormal synchronization between brain networks encoding the somatosensory, affective and cognitive dimensions of pain, and that multisite, closed-loop DBS provides an intuitive mechanism for disrupting that synchrony. By (1) identifying biomarkers of the subjective pain experience and (2) integrating these signals into a state-space representation of pain, we can create a predictive model of each patient's pain experience. Then, by establishing how stimulation in different brain regions influences individual neural signals, we can design real-time, closed-loop therapies tailored to each patient. While chronic pain is a complex disorder that has eluded modern therapies, rich historical data and state-of-the-art technology can now be used to develop a promising treatment. PMID:29632482

Adaptive tracking control for active suspension systems with non-ideal actuators

NASA Astrophysics Data System (ADS)

Pan, Huihui; Sun, Weichao; Jing, Xingjian; Gao, Huijun; Yao, Jianyong

2017-07-01

As a critical component of transportation vehicles, active suspension systems are instrumental in the improvement of ride comfort and maneuverability. However, practical active suspensions commonly suffer from parameter uncertainties (e.g., the variations of payload mass and suspension component parameters), external disturbances and especially the unknown non-ideal actuators (i.e., dead-zone and hysteresis nonlinearities), which always significantly deteriorate the control performance in practice. To overcome these issues, this paper synthesizes an adaptive tracking control strategy for vehicle suspension systems to achieve suspension performance improvements. The proposed control algorithm is formulated by developing a unified framework of non-ideal actuators rather than a separate way, which is a simple yet effective approach to remove the unexpected nonlinear effects. From the perspective of practical implementation, the advantages of the presented controller for active suspensions include that the assumptions on the measurable actuator outputs, the prior knowledge of nonlinear actuator parameters and the uncertain parameters within a known compact set are not required. Furthermore, the stability of the closed-loop suspension system is theoretically guaranteed by rigorous mathematical analysis. Finally, the effectiveness of the presented adaptive control scheme is confirmed using comparative numerical simulation validations.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Reinforcement learning neural-network-based controller for nonlinear discrete-time systems with input constraints.

PubMed

He, Pingan; Jagannathan, S

2007-04-01

A novel adaptive-critic-based neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of nonlinear systems in the presence of actuator constraints. The constraints of the actuator are treated in the controller design as the saturation nonlinearity. The adaptive critic NN controller architecture based on state feedback includes two NNs: the critic NN is used to approximate the "strategic" utility function, whereas the action NN is employed to minimize both the strategic utility function and the unknown nonlinear dynamic estimation errors. The critic and action NN weight updates are derived by minimizing certain quadratic performance indexes. Using the Lyapunov approach and with novel weight updates, the uniformly ultimate boundedness of the closed-loop tracking error and weight estimates is shown in the presence of NN approximation errors and bounded unknown disturbances. The proposed NN controller works in the presence of multiple nonlinearities, unlike other schemes that normally approximate one nonlinearity. Moreover, the adaptive critic NN controller does not require an explicit offline training phase, and the NN weights can be initialized at zero or random. Simulation results justify the theoretical analysis.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

NASA Astrophysics Data System (ADS)

Yoo, Sung Jin

2016-11-01

This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

PubMed

Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

2010-11-01

The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength.

A dual closed-loop control system for mechanical ventilation.

PubMed

Tehrani, Fleur; Rogers, Mark; Lo, Takkin; Malinowski, Thomas; Afuwape, Samuel; Lum, Michael; Grundl, Brett; Terry, Michael

2004-04-01

Closed-loop mechanical ventilation has the potential to provide more effective ventilatory support to patients with less complexity than conventional ventilation. The purpose of this study was to investigate the effectiveness of an automatic technique for mechanical ventilation. Two closed-loop control systems for mechanical ventilation are combined in this study. In one of the control systems several physiological data are used to automatically adjust the frequency and tidal volume of breaths of a patient. This method, which is patented under US Patent number 4986268, uses the criterion of minimal respiratory work rate to provide the patient with a natural pattern of breathing. The inputs to the system include data representing CO2 and O2 levels of the patient as well as respiratory compliance and airway resistance. The I:E ratio is adjusted on the basis of the respiratory time constant to allow for effective emptying of the lungs in expiration and to avoid intrinsic positive end expiratory pressure (PEEP). This system is combined with another closed-loop control system for automatic adjustment of the inspired fraction of oxygen of the patient. This controller uses the feedback of arterial oxygen saturation of the patient and combines a rapid stepwise control procedure with a proportional-integral-derivative (PID) control algorithm to automatically adjust the oxygen concentration in the patient's inspired gas. The dual closed-loop control system has been examined by using mechanical lung studies, computer simulations and animal experiments. In the mechanical lung studies, the ventilation controller adjusted the breathing frequency and tidal volume in a clinically appropriate manner in response to changes in respiratory mechanics. The results of computer simulations and animal studies under induced disturbances showed that blood gases were returned to the normal physiologic range in less than 25 s by the control system. In the animal experiments understeady-state conditions, the maximum standard deviations of arterial oxygen saturation and the end-tidal partial pressure of CO2 were +/- 1.76% and +/- 1.78 mmHg, respectively. The controller maintained the arterial blood gases within normal limits under steady-state conditions and the transient response of the system was robust under various disturbances. The results of the study have showed that the proposed dual closed-loop technique has effectively controlled mechanical ventilation under different test conditions.

The Effects of Closed-Loop Medical Devices on the Autonomy and Accountability of Persons and Systems.

PubMed

Kellmeyer, Philipp; Cochrane, Thomas; Müller, Oliver; Mitchell, Christine; Ball, Tonio; Fins, Joseph J; Biller-Andorno, Nikola

2016-10-01

Closed-loop medical devices such as brain-computer interfaces are an emerging and rapidly advancing neurotechnology. The target patients for brain-computer interfaces (BCIs) are often severely paralyzed, and thus particularly vulnerable in terms of personal autonomy, decisionmaking capacity, and agency. Here we analyze the effects of closed-loop medical devices on the autonomy and accountability of both persons (as patients or research participants) and neurotechnological closed-loop medical systems. We show that although BCIs can strengthen patient autonomy by preserving or restoring communicative abilities and/or motor control, closed-loop devices may also create challenges for moral and legal accountability. We advocate the development of a comprehensive ethical and legal framework to address the challenges of emerging closed-loop neurotechnologies like BCIs and stress the centrality of informed consent and refusal as a means to foster accountability. We propose the creation of an international neuroethics task force with members from medical neuroscience, neuroengineering, computer science, medical law, and medical ethics, as well as representatives of patient advocacy groups and the public.

Closed loop statistical performance analysis of N-K knock controllers

NASA Astrophysics Data System (ADS)

Peyton Jones, James C.; Shayestehmanesh, Saeed; Frey, Jesse

2017-09-01

The closed loop performance of engine knock controllers cannot be rigorously assessed from single experiments or simulations because knock behaves as a random process and therefore the response belongs to a random distribution also. In this work a new method is proposed for computing the distributions and expected values of the closed loop response, both in steady state and in response to disturbances. The method takes as its input the control law, and the knock propensity characteristic of the engine which is mapped from open loop steady state tests. The method is applicable to the 'n-k' class of knock controllers in which the control action is a function only of the number of cycles n since the last control move, and the number k of knock events that have occurred in this time. A Cumulative Summation (CumSum) based controller falls within this category, and the method is used to investigate the performance of the controller in a deeper and more rigorous way than has previously been possible. The results are validated using onerous Monte Carlo simulations, which confirm both the validity of the method and its high computational efficiency.

Generation of dark hollow beam via coherent combination based on adaptive optics.

PubMed

Zheng, Yi; Wang, Xiaohua; Shen, Feng; Li, Xinyang

2010-12-20

A novel method for generating a dark hollow beam (DHB) is proposed and studied both theoretically and experimentally. A coherent combination technique for laser arrays is implemented based on adaptive optics (AO). A beam arraying structure and an active segmented mirror are designed and described. Piston errors are extracted by a zero-order interference detection system with the help of a custom-made photo-detectors array. An algorithm called the extremum approach is adopted to calculate feedback control signals. A dynamic piston error is imported by LiNbO₃ to test the capability of the AO servo. In a closed loop the stable and clear DHB is obtained. The experimental results confirm the feasibility of the concept.