Observer-Based Fuzzy Adaptive Dynamic Surface Control of Uncertain Nonstrict Feedback Systems With Unknown Control Direction and Unknown Dead-Zone

被引:68
作者
Shojaei, Fatemeh [1 ]
Arefi, Mohammad Mehdi [1 ]
Khayatian, Alireza [1 ]
Karimi, Hamid Reza [2 ]
机构
[1] Shiraz Univ, Sch Elect & Comp Engn, Dept Power & Control Engn, Shiraz 7194684636, Iran
[2] Politecn Milan, Dept Mech Engn, I-20156 Milan, Italy
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2019年 / 49卷 / 11期
关键词
Barrier Lyapunov function; fuzzy logic; nonstrict feedback systems; Nussbaum functions; observer-based control; NEURAL-NETWORK CONTROL; NONLINEAR-SYSTEMS; STATE;
D O I
10.1109/TSMC.2018.2852725
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, an observer-based fuzzy adaptive controller for a class of uncertain nonstrict nonlinear systems with unknown control direction and unknown dead-zone is presented. First, by using equivalence dead-zone inverse and a linear state transformation, the original system is converted to a new one. Then, by using fuzzy logic systems, the unknown nonlinearities are approximated based on an adaptive mechanism, and a nonlinear fuzzy state observer is designed to estimate immeasurable states. The dynamic surface control technique is employed to solve the problem of explosion of complexity in the traditional backstepping approach, and then, this method is combined with Nussbaum gain function to address the problem of unknown control direction. Besides, barrier Lyapunov function is employed to overcome the violation of system output. The proposed controller guarantees that the closed-loop system is stable; all the system states are bounded, and tracking errors converge to a neighborhood of the origin. A numerical simulation is provided to confirm the usefulness of the proposed control design.
引用
收藏
页码:2340 / 2351
页数:12
相关论文
共 45 条
[1]   Adaptive model predictive control for constrained nonlinear systems [J].
Adetol, Veronica ;
DeHaan, Darryl ;
Guay, Martin .
SYSTEMS & CONTROL LETTERS, 2009, 58 (05) :320-326
[2]  
[Anonymous], 1996, NONLINEAR SYSTEM
[3]  
[Anonymous], 1991, APPL NONLINEAR CONTR
[4]   Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction [J].
Arefi, Mohammad M. ;
Zarei, Jafar ;
Karimi, Hamid R. .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2014, 351 (08) :4302-4316
[5]   Adaptive Neural Stabilizing Controller for a Class of Mismatched Uncertain Nonlinear Systems by State and Output Feedback [J].
Arefi, Mohammad Mehdi ;
Jahed-Motlagh, Mohammad Reza ;
Karimi, Hamid Reza .
IEEE TRANSACTIONS ON CYBERNETICS, 2015, 45 (08) :1587-1596
[6]   Observer-Based Adaptive Fuzzy Control for a Class of Nonlinear Delayed Systems [J].
Chen, Bing ;
Lin, Chong ;
Liu, Xiaoping ;
Liu, Kefu .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2016, 46 (01) :27-36
[7]   Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form [J].
Chen, Bing ;
Zhang, Huaguang ;
Lin, Chong .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (01) :89-98
[8]  
Chen BS, 1996, IEEE T FUZZY SYST, V4, P32, DOI 10.1109/91.481843
[9]   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
[10]   Decentralized output-feedback neural control for systems with unknown interconnections [J].
Chen, Weisheng ;
Li, Junmin .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2008, 38 (01) :258-266