Small-gain technique-based adaptive fuzzy command filtered control for uncertain nonlinear systems with unmodeled dynamics and disturbances

被引:50
作者
Li, Yulin [1 ]
Xu, Ning [2 ]
Niu, Ben [3 ]
Chang, Yi [1 ]
Zhao, Jinfeng [4 ]
Zhao, Xudong [5 ]
机构
[1] Bohai Univ, Coll Control Sci & Engn, Jinzhou 121013, Liaoning, Peoples R China
[2] Bohai Univ, Coll Informat Sci & Technol, Jinzhou, Peoples R China
[3] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Peoples R China
[4] Harbin Modern Applicat Technol Secondary Vocat Sc, Harbin, Peoples R China
[5] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian, Peoples R China
关键词
adaptive fuzzy control; backstepping; command filter; small-gain approach; unmodeled dynamics; OUTPUT-FEEDBACK CONTROL; TRACKING CONTROL; SURFACE CONTROL; DESIGN; OBSERVER; THEOREM; LOGIC;
D O I
10.1002/acs.3283
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article studies the adaptive tracking control problem for a class of uncertain nonlinear systems with unmodeled dynamics and disturbances. First, a fuzzy state observer is established to estimate unmeasurable states. To overcome the problem of calculating explosion caused by the repeated differentiation of the virtual control signals, the command filter with a compensation mechanism is applied to the controller design procedure. Meanwhile, with the help of the fuzzy logic systems and the backstepping technique, an adaptive fuzzy control scheme is proposed, which guarantees that all signals in the closed-loop systems are bounded, and the tracking error can converge to a small region around the origin. Furthermore, the stability of the systems is proven to be input-to-state practically stable based on the small-gain theorem. Finally, a simulation example verifies the effectiveness of the proposed control approach.
引用
收藏
页码:1664 / 1684
页数:21
相关论文
共 57 条
[1]   A survey of iterative learning control [J].
Bristow, Douglas A. ;
Tharayil, Marina ;
Alleyne, Andrew G. .
IEEE CONTROL SYSTEMS MAGAZINE, 2006, 26 (03) :96-114
[2]   Observer-Based Adaptive Finite-Time Tracking Control for a Class of Switched Nonlinear Systems With Unmodeled Dynamics [J].
Chang, Yi ;
Zhang, Shuo ;
Alotaibi, N. D. ;
Alkhateeb, A. F. .
IEEE ACCESS, 2020, 8 :204782-204790
[3]   Adaptive fuzzy output-feedback tracking control for switched stochastic pure-feedback nonlinear systems [J].
Chang, Yi ;
Wang, Yuanqing ;
Alsaadi, Fuad E. ;
Zong, Guangdeng .
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2019, 33 (10) :1567-1582
[4]   Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form [J].
Chen, Bing ;
Lin, Chong ;
Liu, Xiaoping ;
Liu, Kefu .
IEEE TRANSACTIONS ON CYBERNETICS, 2015, 45 (12) :2744-2755
[5]  
Chen BS, 1996, IEEE T FUZZY SYST, V4, P32, DOI 10.1109/91.481843
[6]   Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems [J].
Chen, Ming ;
Wang, Huanqing ;
Liu, Xiaoping .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) :664-673
[7]   Model-Based adaptive event-Triggered control of nonlinear continuous-Time systems [J].
Chen, Zhongyu ;
Niu, Ben ;
Zhao, Xudong ;
Zhang, Liang ;
Xu, Ning .
APPLIED MATHEMATICS AND COMPUTATION, 2021, 408
[8]   Command Filtered Adaptive Backstepping [J].
Dong, Wenjie ;
Farrell, Jay A. ;
Polycarpou, Marios M. ;
Djapic, Vladimir ;
Sharma, Manu .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (03) :566-580
[9]   Command Filtered Backstepping [J].
Farrell, Jay A. ;
Polycarpou, Marios ;
Sharma, Manu ;
Dong, Wenjie .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2009, 54 (06) :1391-1395
[10]   DESIGN OF SOFTER ROBUST NONLINEAR CONTROL LAWS [J].
FREEMAN, RA ;
KOKOTOVIC, PV .
AUTOMATICA, 1993, 29 (06) :1425-1437