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APPLICATION OF AVERAGING METHOD FOR INTEGRODIFFERENTIAL EQUATIONS TO model-reference adaptive-control OF PARABOLIC-SYSTEMS

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AUTOMATICA 1994年第9期30卷 1415-1419页

作者： HONG, KS BENTSMAN, J UNIV ILLINOIS DEPT MECH & IND ENGN URBANA IL 61801 USA

An averaging theorem for integro-differential equations is applied to the convergence analysis of controller parameters of a model reference adapative control (MRAC) algorithm for a class of parabolic partial differen... 详细信息

关键词： model reference adaptive control AVERAGING METHOD PARTIAL DIFFERENTIAL EQUATION CONVERGENCE ANALYSIS STABILITY

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An optimum model reference adaptive control algorithm for smart base-isolated structures

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BULLETIN OF EARTHQUAKE ENGINEERING 2018年第11期16卷 5647-5670页

作者： Zhang, Dongbin Pan, Peng Zeng, Yi Tsinghua Univ Dept Civil Engn Beijing 100084 Peoples R China Tsinghua Univ China Educ Minist Key Lab Civil Engn Safety & Durabil Beijing 100084 Peoples R China Tsinghua Univ Inst Internet Ind Beijing 100084 Peoples R China

In structural control, appropriate control parameters and a stable closed-loop mechanism are required for a controller to achieve optimal performance, particularly in the presence of uncertain structural parameters under external excitation. In this study, an optimum model reference adaptive control (OMRAC) algorithm combining the Linear quadratic regulator method and model reference adaptive control based on Lyapunov stability is proposed. The OMRAC algorithm is implemented and applied to the response control of a base-isolated structure equipped with magneto-rheological dampers under earthquake excitations. The results from a series of numerical simulations that consider the effects of uncertainty within structural parameters are reported. The performance of the OMRAC algorithm is compared with that of other control algorithms in terms of effectiveness and stability. The results suggest that the proposed OMRAC method can successfully compensate for uncertainties in structural parameters, leading the controlled structure to adaptively track the optimal response of the reference model.

关键词： model reference adaptive control Linear quadratic regulator (LQR) Lyapunov stability Base-isolated structure Magneto-rheological (MR) damper

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A qualitative approach to model reference adaptive control (QMRAC)

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 1998年第2期11卷 269-278页

作者： Leitch, R Keller, U Reay, D Heriot Watt Univ Dept Elect & Comp Engn Intelligent Syst Lab Edinburgh EH14 4AS Midlothian Scotland

This paper proposes a new approach for utilizing qualitative simulation techniques within a model reference adaptive system for the control of ill-defined and uncertain processes, typical of the process industries. It is argued that the practical specification of performance of industrial systems is very often imprecise and multi-valued leading to non-unique (numerical) descriptions of the reference behaviour and, further, that the lack of precise knowledge of the industrial process results in inaccurate (numerical) models of the process to be controlled. This can lead to significant deterioration in performance with respect to the desired specification necessitating empirical tuning and hence the loss of analytic properties. Qualitative simulation techniques are used to model imprecise specifications and process knowledge, and hence to generate the reference behaviour without a loss of accuracy with respect to the original specifications. The discrepancy between the actual and the reference behaviour is used to adapt a conventional control algorithm such that model-following behaviour is maintained in the face of significant disturbance to the normal behaviour. Results are presented for first- and second-order models of desired specifications. The results are very encouraging, demonstrating that accurate adaptive behaviour of ill-defined systems can be obtained without the need to corrupt. or approximate, the original specifications, and without necessitating the availability of accurate, high-order, numerical models. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： qualitative simulation uncertain dynamic systems model reference adaptive control

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PdE-based model reference adaptive control of uncertain heterogeneous multiagent networks

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NONLINEAR ANALYSIS-HYBRID SYSTEMS 2008年第4期2卷 1152-1167页

作者： Kim, Jun Kim, Kyoung-Dae Natarajan, Vivek Kelly, Scott David Bentsman, Joseph Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Univ N Carolina Dept Mech Engn & Engn Sci Charlotte NC 28223 USA

Robust globally stable model reference adaptive control (MRAC) laws recently derived for systems described by parabolic and hyperbolic partial differential equations (PDEs) with spatially-varying coefficients under distributed sensing and actuation are extended to heterogeneous multiagent networks characterized by parameter uncertainty. The extension is carried out using partial difference equations (PdEs) on graphs that preserve parabolic- and hyperbolic-like cumulative network behavior. Unlike in the PDE case, only boundary input is specified for the reference model. The algorithms proposed directly incorporate this boundary reference input into the reference PdE to generate the distributed admissible reference evolution profile followed by the agents. The agent evolution thus depends only on the interaction with the adjacent agents, making the system fully decentralized. Numerical examples are presented as well, including the case of the switched topology associated with a sudden loss of an agent. The resulting PdE MRAC laws inherit the robust linear structure of their PDE counterparts. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： model reference adaptive control Decentralized control Multiagent networks Partial difference equations on graphs Parameter uncertainty

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Application of model reference adaptive control to industrial robot impedance control

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 1998年第2期22卷 153-163页

作者： Kamnik, R Matko, D Bajd, T Univ Ljubljana Fac Elect Engn Ljubljana Slovenia

The paper deals with the application of model reference adaptive control to robot impedance control, which is actually a technique of steering the end-effector on a prescribed path and satisfying a prescribed dynamic relationship between the force and the end-effector position. Due to unknown parameters of the environment (stiffness, exact position), a model reference algorithm is proposed which differs from classical algorithms in its method of excitation. The results of the proposed procedure are illustrated by implementation on the ASEA IRb 6 industrial robot.

关键词： industrial robots robot impedance control model reference adaptive control constrained motion

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sEMG-based variable impedance control of lower-limb rehabilitation robot using wavelet neural network and model reference adaptive control

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INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION 2020年第3期47卷 349-358页

作者： Hasanzadeh Fereydooni, Rohollah Siahkali, Hassan Shayanfar, Heidar Ali Mazinan, Amir Houshang Islamic Azad Univ Dept Elect Engn South Tehran Branch Tehran Iran

Purpose This paper aims to propose an innovative adaptive control method for lower-limb rehabilitation robots. Design/methodology/approach Despite carrying out various studies on the subject of rehabilitation robots, the flexibility and stability of the closed-loop control system is still a challenging problem. In the proposed method, surface electromyography (sEMG) and human force-based dual closed-loop control strategy is designed to adaptively control the rehabilitation robots. A motion analysis of human lower limbs is performed by using a wavelet neural network (WNN) to obtain the desired trajectory of patients. In the outer loop, the reference trajectory of the robot is modified by a variable impedance controller (VIC) on the basis of the sEMG and human force. Thenceforward, in the inner loop, a model reference adaptive controller with parameter updating laws based on the Lyapunov stability theory forces the rehabilitation robot to track the reference trajectory. Findings The experiment results confirm that the trajectory tracking error is efficiently decreased by the VIC and adaptively correct the reference trajectory synchronizing with the patients' motion intention;the model reference controller is able to outstandingly force the rehabilitation robot to track the reference trajectory. The method proposed in this paper can better the functioning of the rehabilitation robot system and is expandable to other applications of the rehabilitation field. Originality/value The proposed approach is interesting for the design of an intelligent control of rehabilitation robots. The main contributions of this paper are: using a WNN to obtain the desired trajectory of patients based on sEMG signal, modifying the reference trajectory by the VIC and using model reference control to force rehabilitation robot to track the reference trajectory.

关键词： Rehabilitation robot Surface electromyography model reference adaptive control Variable impedance controller

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model reference adaptive control for Manipulators–A Review

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IFAC Proceedings Volumes 1985年第16期18卷 111-116页

作者： I.H. Mufti Division of Mechanical Engineering National Research Council of Canada Ottawa Canada K1A 0R6

Based on the model reference approach and Popov's hyperstability theory, several adaptive control laws are derived in a simple and unified manner. The concepts of hyperstabi1ity theory and model reference adaptive control systems are introduced by means of a first order constant linear system. The theory is then applied to the design of adaptive controllers for manipulators having complex and nonlinear dynamics.

关键词： adaptive control model reference adaptive control hyperstability industrial robots nonlinear control systems

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Enhanced model reference adaptive control based on data-driven technique for permanent magnet synchronous motors with uncertainties

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Journal of Engineering Science and Technology Review 2017年第4期10卷 72-80页

作者： Qiao, Feng Liu, Zhizhen Zong, Kun School of Electrical Engineering Shandong University Jinan250061 China UFR Sciences et Techniques Université du Havre Le Havre76600 France

Precise velocity control of permanent magnet synchronous motors (PMSMs) is challenging due to the uncertainties induced by the mathematical model, unmodeled dynamics, and various disturbances;consequently, the traditional model reference adaptive control (MRAC) for PMSMs becomes questionable. In order to improve the traditional MRAC and lessen the influence of various sources of uncertainty, this study proposes an enhanced MRAC approach based on datadriven technique. First, the approach established an equivalent differential expression linear model for the discrete-time nonlinear description of PMSM and designed a data-driven controller using a model-free adaptive technique. This design depended on the unique bounded parameter referred as pseudo-partial-derivative (PPD) that was a slowly time-varying parameter relating to the system action point or system dynamics. Second, the approach identified the parameter PPD using Popov criterion to ensure the asymptotic stability of the controlled system. Finally, the approach was simulated and applied on a 50 kW PMSM drive of Toyota Prius II hybrid electric vehicles to demonstrate the effects of different control parameters. Results show that the proposed approach does not suffer from the drawback of the modeling process and unmodeled dynamics and provides improved velocity-tracking precision against parameter variations and external disturbances. When the weight factor increases from 0.1 to 1 or the pseudo-orders from 1 to 5, the velocity presents high robustness. Moreover, the approach yields satisfactory disturbance rejection and fault tolerance compared with the traditional MRAC even if some input and output (I/O) data are missing. This study solves the problem of dependence on plant models for the traditional MRAC and achieves better suppression of uncertainties, demonstrating the effective applications of this approach for actual nonlinear motor systems with uncertainties. © 2017 Eastern Macedonia and Thrace Institute

关键词： model reference adaptive control

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Discrete-time model reference adaptive control for nonminimum phase systems with disturbances using approximate inverse systems

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IEE PROCEEDINGS-control THEORY AND APPLICATIONS 1997年第5期144卷 447-454页

作者： Lu, J Yahagi, T Chiba Univ Dept Informat & Comp Sci Chiba 263 Japan

A new design method of discrete-time model reference adaptive control for nonminimum phase systems is presented, with disturbances using approximate inverse systems obtained from the long division method. It is assumed that the disturbances are described by a polynomial function of time with known degree and unknown coefficients. The proposed scheme uses only input and output data, and the existence of bounds for all signals is proved. This scheme also assures that plant output converges to the reference model output. The results of computer simulation are also presented to illustrate the effectiveness of the proposed method.

关键词： discrete-time model reference adaptive control nonminimum phase systems approximate inverse systems

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A new approach to model reference adaptive control

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IEEE TRANSACTIONS ON AUTOMATIC control 2003年第5期48卷 743-757页

作者： Miller, DE Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

In classical model reference adaptive control, the goal is to design a controller to make the closed-loop system act like a prespecified reference model in the face of significant plant uncertainty. Typically, the controller consists of an identifier (or tuner) which is used to adjust the parameters of a linear time-invariant (LTI) compensator, and under suitable assumptions on the plant model uncertainty it is proven that asymptotic matching is achieved. However, the controller is typically highly nonlinear, and the closed loop system can exhibit undesirable behavior, such as large transients or a large control signal, especially if the initial parameter estimates are poor. Furthermore, its ability to tolerate time-varying parameters is typically limitted. Here, we propose an alternative approach. Rather than estimating the plant or compensator parameters, instead we estimate what the control signal would be if the plant parameters and plant state were known and the "Ideal LTI compensator" were applied;we end up with a linear periodic controller. Our assumptions are reasonably natural extensions of the classical ones to the time-varying setting;we allow rapid parameter variations, although we add a compactness requirement. We prove that we can obtain arbitrarily good tracking, we explore the benefits and limitations of the approach, and we provide a simulation study.

关键词： adaptive control linear time-varying control model reference adaptive control

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