Adaptive fuzzy approach for a class of uncertain nonlinear systems in strict-feedback form

被引：60
作者：
Ho, H. F. [1 ]
Wong, Y. K. [1 ]
Rad, A. B. [2 ]
机构：
[1] Hong Kong Polytech Univ, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
[2] Simon Fraser Univ, Burnaby, BC V5A 1S6, Canada
来源：
ISA TRANSACTIONS | 2008年 / 47卷 / 03期
关键词：
adaptive control; backstepping; fuzzy control; uncertain nonlinear systems;
D O I：
10.1016/j.isatra.2008.03.002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Adaptive fuzzy control is proposed for a class of affine nonlinear systems in strict-feedback form with unknown nonlinearities. The unknown nonlinearities include two types of nonlinear functions: one satisfies the "triangularity condition" and can be directly approximated by fuzzy logic system, while the other is assumed to be partially known and consists of parametric uncertainties. Takagi-Sugeno type fuzzy approximators are used to approximate unknown system nonlinearities and the design procedure is a combination of adaptive backstepping and generalized small gain design techniques. It is proved that the proposed adaptive control scheme can guarantee the uniformly ultimately bounded (UBB) stability of the closed-loop systems. Simulation studies are shown to illustrate the effectiveness of the proposed approach. (C) 2008, ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：286 / 299
页数：14
相关论文
共 38 条
  • [1] [Anonymous], 1989, ROBOT DYNAMIC CONTRO
  • [2] Chen BS, 1996, IEEE T FUZZY SYST, V4, P32, DOI 10.1109/91.481843
  • [3] Choi JY, 2001, IEEE T NEURAL NETWOR, V12, P1103, DOI 10.1109/72.950139
  • [4] Integrator backstepping control of a brush DC motor turning a robotic load
    Dawson, D.M.
    Carroll, J.J.
    Schneider, M.
    [J]. IEEE Transactions on Control Systems Technology, 1994, 2 (03) : 233 - 244
  • [5] Adaptive neural network control of nonlinear systems with unknown time delays
    Ge, SS
    Hong, F
    Lee, TH
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2003, 48 (11) : 2004 - 2010
  • [6] GE SS, 2002, IEEE T NEURAL NETWOR, V13, P837
  • [7] Robust backstepping control for a class of time delayed systems
    Hua, CC
    Guan, XP
    Shi, P
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2005, 50 (06) : 894 - 899
  • [8] Robust output feedback tracking control for time-delay nonlinear systems using neural network
    Hua, Changchun
    Guan, Xinping
    Shi, Peng
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (02): : 495 - 505
  • [9] Ioannou PA., 1996, ROBUST ADAPTIVE CONT, V1
  • [10] Isidori A, 1995, NONLINEAR CONTROL SYSTEMS DESIGN 1995, VOLS 1 AND 2, P87
1234