Adaptive fuzzy logic control of discrete-time dynamical systems

被引:59
作者
Jagannathan, S
Vandegrift, MW
Lewis, FL
机构
[1] Univ Texas, Dept Elect Engn, San Antonio, TX 78249 USA
[2] Texas Instruments Inc, Intelligent Syst Grp, Dallas, TX USA
[3] Univ Texas, Automat & Robot Res Inst, Ft Worth, TX 76118 USA
基金
美国国家科学基金会;
关键词
fuzzy logic; discrete-time control; adaptive control; fuzzy approximation; universal fuzzy controller;
D O I
10.1016/S0005-1098(99)00143-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The objective of this paper is to achieve tracking control of a class of unknown nonlinear dynamical systems using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLCs are implemented on digital computers. We present a repeatable design algorithm and a stability proof for an adaptive fuzzy logic controller that uses basis vectors based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant (e.g. a tediously computed "regression matrix"). An E-modification sort of approach to adapt the fuzzy system parameters was selected. With mild assumptions on the class of discrete-time nonlinear systems, this adaptive fuzzy logic controller guarantees uniform ultimate boundedness of the closed-loop signals and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that works for a more general class of nonlinear systems. Some new passivity properties of fuzzy logic systems are introduced. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:229 / 241
页数:13
相关论文
共 10 条
[1]   UNIVERSAL FUZZY CONTROLLERS [J].
BUCKLEY, JJ .
AUTOMATICA, 1992, 28 (06) :1245-1248
[2]   Discrete-time neural net controller for a class of nonlinear dynamical systems [J].
Jagannathan, S ;
Lewis, FL .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1996, 41 (11) :1693-1699
[3]   FUZZY-SYSTEMS AS UNIVERSAL APPROXIMATORS [J].
KOSKO, B .
IEEE TRANSACTIONS ON COMPUTERS, 1994, 43 (11) :1329-1333
[4]   Towards a paradigm for fuzzy logic control [J].
Lewis, FL ;
Liu, K .
AUTOMATICA, 1996, 32 (02) :167-181
[5]  
LEWIS FL, 1995, PROCEEDINGS OF THE 1995 AMERICAN CONTROL CONFERENCE, VOLS 1-6, P3760
[6]   A NEW ADAPTIVE LAW FOR ROBUST ADAPTATION WITHOUT PERSISTENT EXCITATION [J].
NARENDRA, KS ;
ANNASWAMY, AM .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1987, 32 (02) :134-145
[7]  
VANDEGRIFT MW, 1995, PROCEEDINGS OF THE 1995 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL, P395, DOI 10.1109/ISIC.1995.525089
[8]   FUZZY BASIS FUNCTIONS, UNIVERSAL APPROXIMATION, AND ORTHOGONAL LEAST-SQUARES LEARNING [J].
WANG, LX ;
MENDEL, JM .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1992, 3 (05) :807-814
[9]   SUFFICIENT CONDITIONS ON GENERAL FUZZY-SYSTEMS AS FUNCTION APPROXIMATORS [J].
YING, H .
AUTOMATICA, 1994, 30 (03) :521-525
[10]   APPROXIMATION-THEORY OF FUZZY-SYSTEMS - MIMO CASE [J].
ZENG, XJ ;
SINGH, MG .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1995, 3 (02) :219-235