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STATE DERIVATIVE-FREE VARIABLE STRUCTURE model reference adaptive control OF LINEAR PARABOLIC SYSTEMS

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Journal of Systems Science & Complexity 2013年第6期26卷 957-967页

作者： JIA Chaohua SHAO Zhi-Chao School of Mathematics and Systems Science Beihang University Department of Applied Mathematics School of StatisticsUniversity of International Business and Economics

The problem of constructing a model dimensional parabolic system is considered in this reference adaptive control law for an uncertain 1- article. The controller designed here involves only the plant state but no its derivatives. A priori bounds on the plant＇s uncertain parameters are used to propose switching laws which serve as an adaptive mechanism. The exponential decay to zero of the state error with any prescribed rate is guaranteed by choosing a controller parameter correspondingly. Numerical studies are also presented to illustrate the applicability of the control law.

关键词： Distributed parameter systems model reference adaptive control parabolicsystems.

Application of a Robust model reference adaptive control Algorithm to a Nonlinear Automotive Actuator

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International Journal of Automation and computing 2014年第4期11卷 377-391页

作者： Alessandro di Gaeta Umberto Montanaro Istituto Motori National Research Council Naples Italy

model reference adaptive control is a viable control method to impose the demanded dynamics on plants whose parameters are affected by large uncertainty. In this paper, we show by means of experiments that robust adaptive methods can effectively face nonlinearities that are common to many automotive electromechanical devices. We consider here, as a representative case study, the control of a strongly nonlinear automotive actuator. The experimental results confirm the effectiveness of the method to cope with unmodeled nonlinear terms and unknown parameters. In addition, the engineering performance indexes computed on experimental data clearly show that the robust adaptive strategy provides better performance compared with those given by a classical model-based control solution with fixed gains.

关键词： model reference adaptive control robust adaptive control nonlinear systems automotive control electronic throttle body electromechanical actuators

Direct model reference adaptive control using K_p = LDU factorization for multivariable discrete-time plants

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控制理论与应用（英文版） 2008年第4期6卷 392-398页

作者： Junling LI Xuejun XIE Wei CHEN Institute of Automation Qufu Normal University Qufu Shandong 273165 China

For a large class of discrete-time multivariable plants with arbitrary relative degrees, the design and analysis of the direct model reference adaptive control scheme are investigated under less restrictive assumptions. The algorithm is based on a new parametrization derived from the high frequency gain matrix factorization Kp=LDU under the condition that the signs of the leading principal minors of/fp are known. By reproving the discrete-time Lp and L2σ norm relationship between inputs and outputs, establishing the properties of discrete-time adaptive law, defining the normalizing signal, and relating the signal with all signals in the closed-loop system, the stability and convergence of the discrete-time multivariable model reference adaptive control scheme are analyzed rigorously in a systematic fashion as in the continuous-time case.

关键词： Discrete-time systems Swapping lemma L2σ-nonn Normalizing signal model reference adaptive control

State tracking model reference adaptive control for switched nonlinear systems with linear uncertain parameters

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控制理论与应用（英文版） 2012年第3期10卷 354-358页

作者： Xia WANG Jun ZHAO Yujun TANG State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Liaoning 110004 China College of Electronic and Informational Engineering Hebei University Baoding Hebei 071002 China

model reference adaptive control （MRAC） is considered for a class of switched nonlinear systems in which the unknown parameters appear linearly. The linear uncertain parameters in each subsystem can be expressed as a vector and the uncertain vectors in different subsystems are estimated individually by different vector variables. Update laws are designed such that the parameter estimation will ＇freeze＇ until its corresponding subsystem is active. controllers for subsystems are given to ensure asymptotic states tracking under arbitrary switchings. Two examples are presented to validate the proposed method.

关键词： Switched nonlinear system model reference adaptive control State tracking

MULTIVARIABLE model reference adaptive control FOR A TURBOFAN ENGINE

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Chinese Journal of Aeronautics 1996年第4期9卷 300-304页

作者： Fan Jun Huang Jinquan Sun Jianguo Feng Zhengping(Dep. Of Power Engineering, Nanjing University of Aeronauticsand Astronautics, Nanjing,China, 210026) Dep. of Power Engineering Nanjing Univ. Aero. and Astronaut. Nanjing 210026 China

A decentralized model reference adaptive control (MRAC) scheme is proposed and applied to design a multivariable control system of a dual-spool turbofan *** studies show good static and dynamic performance of the system over the fullflight envelope. Simulation results also show the good effectiveness of reducing interactionin the multivariable system with significant coupling. The control system developed has awide frequency band to satisfy the strict engineering requirement and is practical for engineering applications.

关键词： turbofan engines model reference adaptive control flight envelopes multivariable control

model reference adaptive control for a Class of Aircraft with Actuator Saturation

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Model Reference Adaptive Control for a Class of Aircraft wit...

Direct model reference adaptive control of Periodic Slow Time-Varying Systems with Disturbance Input

第37届中国控制会议

作者： Jiao Chen Jiangyun Wang Weihong Wang School of Automation Science and Electrical Engineering Beihang University

model reference adaptive control（MRAC） is known as a proper method to handle uncertainties of systems and achieve precision command tracking. However, actuator saturation of aircraft limits the ability of the adaptive controller in practice. In this paper, a modified automatic control architecture is presented for a class of aircraft in the presence of input saturation. The proposed controller is based on model reference adaptive control augmented with a modern anti-windup（AW） compensator. First, a standard MRAC with integral state feedback is described. Second, a Riccati-based AW compensator is employed to solve the input saturation problem. Finally, the control technique is applied to control the vertical acceleration of the aircraft with significant uncertainty in control effectiveness and matched uncertainties. Simulation results verify the performance of proposed method.

关键词： model reference adaptive control Actuator saturation Anti-windup Compensator Aircraft

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Direct Model Reference Adaptive Control of Periodic Slow Tim...

ADP-Based model reference adaptive control Design for Unknown Discrete-Time Nonlinear Systems

第43届中国控制会议

作者： Zhuolin Tan Xiaochen Xie Jiantai Huang Department of Automation Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms and adaptive Robotics

This paper investigates the direct model reference adaptive control(MRAC) of periodic systems with slow timevarying dynamics and disturbance input. It is necessary to approximate the periodic slow time-varying system as a periodic piecewise linear system for MRAC. Based on the stability criteria of the periodic piecewise linear reference system, a new sufficient condition in terms of linear matrix inequalities(LMIs) is established to obtain the Lyapunov matrices and design the adaptive update law for the state feedback controller gains. Different from previous studies, where asymptotic tracking was possible only in the presence of a common Lyapunov function for the reference models, the asymptotic tracking in this work is achieved through a periodic time-varying Lyapunov matrix function. A numerical example validates the proposed MRAC scheme, and the effectiveness of the modified approach is discussed.

关键词： model reference adaptive control Periodic Slow Time-Varying System Periodic Piecewise Linear System

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ADP-Based Model Reference Adaptive Control Design for Unknow...

model reference adaptive impedance control for physical human-robot interaction

第37届中国控制会议

作者： Wei Wang Xin Chen Fang Wang Hao Fu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced control and Intelligent Automation for Complex Systems School of Electrical and Information Engineering Zhengzhou University of Light Industry

In engineering applications, it is very useful to make a nonlinear system behave like a linear stable system. However,how to design a model reference adaptive control（MRAC） as the nonlinear dynamics is unknown is the key problem. In this study,an MRAC with adaptive dynamic programming（ADP） algorithm is presented for discrete-time nonlinear unknown dynamic systems, in which a multi-layer neural network（NN） model is utilized to describe the nonlinear system’s dynamics. Then based on this approximate model, a feedforward neuro-controller is developed as the desired control corresponding to the reference input. Third, the iterative ADP algorithm, in the form of actor-critic framework, employs two NNs to estimate the action value function, and generates the feedback control which, together with the feedforward neuro-controller, makes the state of the system track the reference model. Finally the feasibility of the new approach is verified by two numerical experiments.

关键词： model reference adaptive control adaptive dynamic programming Nonlinear system Q-function

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control Theory and Technology 2016年第1期14卷 68-82页

作者： Bakur ALQAUDI Hamidreza MODARES Isura RANATUNGA Shaikh M. TOUSIF Frank L. LEWIS Dan O. POPA The University of Texas at Arlington Research Institute (UTARI) Fort Worth TX 76118 U.S.A. Department of Electrical Engineering College of Engineering The University of Texas at Arlington Arlington TX 76019 U.S.A. Electronics and Instrumentation Engineering Technology Department Yanbu Industrial College P.O. Box 30436 41912 Yanbu al-Sinaiyah K.S.A. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Liaoning 110819 China

This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.

关键词： Human-robot interaction model reference adaptive control model reference neuroadaptive impedance control