Optimal adaptive fuzzy FTC design for strict-feedback nonlinear uncertain systems with actuator faults

被引:28
作者
Sun, Kangkang
Sui, Shuai
Tong, Shaocheng
机构
基金
中国国家自然科学基金;
关键词
Optimal control; Fuzzy adaptive control; Fault-tolerant control; Backstepping technique; Strict-feedback nonlinear systems; CONTINUOUS-TIME SYSTEMS; DYNAMIC SURFACE CONTROL; TOLERANT CONTROL; TRACKING CONTROL;
D O I
10.1016/j.fss.2016.10.007
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, the optimal fault-tolerant control (FTC) design problem is investigated for strict-feedback nonlinear systems. The considered nonlinear systems contain actuator faults, which are bias fault and gain fault. The problem of actuator faults is solved by utilizing the adaptive compensation technique. Applying the backstepping design technique, a main fault-tolerant controller is established. Via the designed main fault-tolerant control strategy, the controlled nonlinear system can be converted to an equivalent nonlinear system in affine form. Subsequently, a fuzzy logic system (FLS) is introduced to approximate the unknown cost function, and an adaptive fuzzy feedback optimal controller is developed. The whole adaptive fuzzy fault-tolerant optimal control scheme consists of a main controller and a feedback optimal controller. Based on the Lyapunov theory, it is proved that all the signals in the closed-loop system are bounded, the system output can track a bounded reference signal. In addition, the proposed control method can guarantee the cost function is the smallest. Simulation results are provided to illustrate the effectiveness of the proposed fault-tolerant optimal control scheme. (C) 2016 Elsevier B. V. All rights reserved.
引用
收藏
页码:20 / 34
页数:15
相关论文
共 38 条
[1]   Adaptive dynamic programming and optimal control of nonlinear nonaffine systems [J].
Bian, Tao ;
Jiang, Yu ;
Jiang, Zhong-Ping .
AUTOMATICA, 2014, 50 (10) :2624-2632
[2]   How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems [J].
Boulkroune, A. ;
Tadjine, M. ;
M'Saad, M. ;
Farza, M. .
FUZZY SETS AND SYSTEMS, 2008, 159 (08) :926-948
[3]   On the design of observer-based fuzzy adaptive controller for nonlinear systems with unknown control gain sign [J].
Boulkroune, A. ;
M'saad, M. .
FUZZY SETS AND SYSTEMS, 2012, 201 :71-85
[4]   Adaptive fuzzy tracking control of nonlinear MIMO systems with time-varying delays [J].
Chen, Bing ;
Liu, Xiaoping ;
Liu, Kefu ;
Lin, Chong .
FUZZY SETS AND SYSTEMS, 2013, 217 :1-21
[5]  
Chen M., 2015, IEEE T CYBERNETICS
[6]   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
[7]   Fuzzy dynamic surface control for uncertain nonlinear systems under input saturation via truncated adaptation approach [J].
Gao, Shigen ;
Ning, Bin ;
Dong, Hairong .
FUZZY SETS AND SYSTEMS, 2016, 290 :100-117
[8]   Direct adaptive NN control of a class of nonlinear systems [J].
Ge, SS ;
Wang, C .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (01) :214-221
[9]   Global Adaptive Dynamic Programming for Continuous-Time Nonlinear Systems [J].
Jiang, Yu ;
Jiang, Zhong-Ping .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (11) :2917-2929
[10]  
Keliris C., 2016, IEEE T NEURAL NETW L