Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

被引:90
作者
Li, Yongming [1 ,2 ]
Tong, Shaocheng [2 ]
Li, Tieshan [1 ]
机构
[1] Dalian Maritime Univ, Nav Coll, Dalian 116026, Liaoning, Peoples R China
[2] Liaoning Univ Technol, Dept Basic Math, Jinzhou 121001, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Uncertain nonlinear systems; Adaptive fuzzy control; Saturation; Backstepping design; Stability analysis; SMALL-GAIN APPROACH; OUTPUT-FEEDBACK CONTROL; TIME-DELAY SYSTEMS; NEURAL-NETWORKS; STABILIZATION;
D O I
10.1007/s00521-012-0993-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a novel direct adaptive fuzzy control approach is presented for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are directly used to tackle unknown nonlinear functions, and the adaptive fuzzy tracking controller is constructed by using the backstepping recursive design techniques. To overcome the problem of input saturation, a new auxiliary design system and Nussbaum gain functions are incorporated into the control scheme, respectively. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. A simulation example is included to illustrate the effectiveness of the proposed approach. Two key advantages of the scheme are that (i) the direct adaptive fuzzy control method is proposed for uncertain nonlinear system with input saturation by using Nussbaum function technique and (ii) The number of the online adaptive learning parameters is reduced.
引用
收藏
页码:1207 / 1216
页数:10
相关论文
共 36 条
[21]   A Combined Backstepping and Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control [J].
Tong, Shao-Cheng ;
He, Xiang-Lei ;
Zhang, Hua-Guang .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2009, 17 (05) :1059-1069
[22]   Fuzzy-Adaptive Decentralized Output-Feedback Control for Large-Scale Nonlinear Systems With Dynamical Uncertainties [J].
Tong, Shaocheng ;
Liu, Changliang ;
Li, Yongming .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2010, 18 (05) :845-861
[23]   Observer-based fuzzy adaptive control for strict-feedback nonlinear systems [J].
Tong, Shaocheng ;
Li, Yongming .
FUZZY SETS AND SYSTEMS, 2009, 160 (12) :1749-1764
[24]  
Wang L.:., 1994, Adaptive Fuzzy System and Control: Desing and Stability Analysis
[25]  
Wang T, 2009, INT J INNOV COMPUT I, V5, P2675
[26]   An LMI Approach to Stability Analysis of Reaction-Diffusion Cohen-Grossberg Neural Networks Concerning Dirichlet Boundary Conditions and Distributed Delays [J].
Wang, Zhanshan ;
Zhang, Huaguang ;
Li, Ping .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 40 (06) :1596-1606
[27]   Global Asymptotic Stability of Reaction-Diffusion Cohen-Grossberg Neural Networks With Continuously Distributed Delays [J].
Wang, Zhanshan ;
Zhang, Huaguang .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (01) :39-49
[28]   Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance [J].
Wen, Changyun ;
Zhou, Jing ;
Liu, Zhitao ;
Su, Hongye .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2011, 56 (07) :1672-1678
[29]   Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations [J].
Wu, Huai-Ning ;
Cai, Kai-Yuan .
INFORMATION SCIENCES, 2007, 177 (06) :1509-1522
[30]   Adaptive fuzzy H∞ stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach [J].
Yang, YS ;
Zhou, CJ .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2005, 13 (01) :104-114