Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints

被引：1028

作者：

Chen, Mou ^{[3
,4
]}

Ge, Shuzhi Sam ^{[1
,2
,4
]}

Ren, Beibei ^{[4
]}

机构：

[1] Univ Elect Sci & Technol China, Inst Intelligent Syst & Informat Technol, Chengdu 611731, Peoples R China

[2] Univ Elect Sci & Technol China, Inst Robot, Chengdu 611731, Peoples R China

[3] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China

[4] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore

来源：

AUTOMATICA | 2011年 / 47卷 / 03期

关键词：

Nonlinear systems; Input constraint; Command filter; Adaptive tracking control; Backstepping control; NEURAL-NETWORK CONTROL; OUTPUT-FEEDBACK CONTROL; DYNAMIC SURFACE CONTROL; TIME-VARYING DELAY; ROBUST-CONTROL; ACTUATOR SATURATION; CONTROL DESIGN; FORM; MANIPULATORS; PLANTS;

D O I：

10.1016/j.automatica.2011.01.025

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, adaptive tracking control is proposed for a class of uncertain multi-input and multi-output nonlinear systems with non-symmetric input constraints. The auxiliary design system is introduced to analyze the effect of input constraints, and its states are used to adaptive tracking control design. The spectral radius of the control coefficient matrix is used to relax the nonsingular assumption of the control coefficient matrix. Subsequently, the constrained adaptive control is presented, where command filters are adopted to implement the emulate of actuator physical constraints on the control law and virtual control laws and avoid the tedious analytic computations of time derivatives of virtual control laws in the backstepping procedure. Under the proposed control techniques, the closed-loop semi-global uniformly ultimate bounded stability is achieved via Lyapunov synthesis. Finally, simulation studies are presented to illustrate the effectiveness of the proposed adaptive tracking control. (c) 2011 Elsevier Ltd. All rights reserved.

引用

页码：452 / 465

页数：14

共 46 条

[1] Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation [J].

Cao, YY ;

Lin, ZL .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2003, 11 (01) :57-67

[2] Robust tracking control for nonlinear MIMO systems via fuzzy approaches [J].

Chang, YC .

AUTOMATICA, 2000, 36 (10) :1535-1545

[3] Adaptive output feedback tracking control for a class of uncertain nonlinear systems using neural networks [J].

Chang, YC ;

Yen, HM .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2005, 35 (06) :1311-1316

[4] An adaptive H∞ tracking control for a class of nonlinear multiple-input-multiple-output (MIMO) systems [J].

Chang, Y.-C. .

2001, Institute of Electrical and Electronics Engineers Inc. (46)

[5]

CHEN M, 2009, P IEEE INT C AUT LOG, P85, DOI DOI 10.1109/ICAL.2009.5262972

[6] Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities [J].

Chen, Mou ;

Ge, Shuzhi Sam ;

How, Bernard Voon Ee .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (05) :796-812

[7] Integrator backstepping control of a brush DC motor turning a robotic load [J].

Dawson, D.M. ;

Carroll, J.J. ;

Schneider, M. .

IEEE Transactions on Control Systems Technology, 1994, 2 (03) :233-244

[8]

Farrell J, 2003, P AMER CONTR CONF, P3898

[9] Neural network control of a class of nonlinear systems with actuator saturation [J].

Gao, WZ ;

Selmic, RR .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (01) :147-156

[10] Approximation-based control of nonlinear MIMO time-delay systems [J].

Ge, S. S. ;

Tee, K. P. .

AUTOMATICA, 2007, 43 (01) :31-43

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