Reduced-order intermediate variable observer based fault estimation and fault-tolerant control for fuzzy stochastic systems with exogenous disturbance

被引:9
|
作者
Wang, Jing [1 ]
Han, Jian [1 ]
Liu, Xiuhua [1 ]
Sun, Shaoxin [2 ]
机构
[1] Ludong Univ, Sch Math & Stat Sci, Yantai 264025, Peoples R China
[2] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Reduced-order intermediate variable; observers; Disturbance observers; Fuzzy stochastic systems; Fault estimation; Fault-tolerant control; NONLINEAR MULTIAGENT SYSTEMS; MARKOV JUMP SYSTEMS; ACTUATOR; SENSOR; DIAGNOSIS; NETWORK; DESIGN;
D O I
10.1016/j.ins.2022.06.030
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 paper studies fault estimation and fault-tolerant control problems for fuzzy systems with exogenous disturbance and stochastic noise. The fuzzy reduced-order intermediate variable observers and the disturbance observers are proposed to reconstruct the sensor fault, the actuator fault and the disturbance. According to the estimated results, the obser-ver based fault-tolerant controllers are devised. Compared with the full-order observer design method, the designed reduced-order observers are with lower dimensions and less cost. Different from the classic intermediate observer, the feedback term of the output esti-mation error is introduced into our observers, which increases the design freedom. And the obtained linear matrix inequality conditions can ensure that the whole closed-loop sys-tems are mean-square exponentially stable. Finally, two examples are offered to verify the feasibility of the proposed method. (c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:202 / 221
页数:20
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