Fault Reconstruction and Fault-Tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems With Time Delays

被引:165
|
作者
Jia, Qingxian [1 ]
Chen, Wen [2 ]
Zhang, Yingchun [1 ,3 ]
Li, Huayi [1 ]
机构
[1] Harbin Inst Technol, Res Ctr Satellite Technol, Harbin 150001, Peoples R China
[2] Wayne State Univ, Div Engn Technol, Detroit, MI 48202 USA
[3] Shenzen Aerosp Dongfanghong HIT Satellite Co Ltd, Shenzhen 518057, Peoples R China
关键词
Fault reconstruction; fault-tolerant control (FTC); learning observers (LOs); linear matrix inequalities (LMIs); Takagi-Sugeno (T-S) fuzzy descriptor systems; UNKNOWN INPUTS; FILTER DESIGN; STABILIZATION; OPTIMIZATION; STABILITY; DIAGNOSIS; MODELS;
D O I
10.1109/TIE.2015.2404784
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 addresses the problems of observer-based fault reconstruction and fault-tolerant control for Takagi-Sugeno fuzzy descriptor systems subject to time delays and external disturbances. A novel fuzzy descriptor learning observer is constructed to achieve simultaneous reconstruction of system states and actuator faults. Sufficient conditions for the existence of the proposed observer are explicitly provided. Utilizing the reconstructed fault information, a reconfigurable fuzzy fault-tolerant controller based on the separation property is designed to compensate for the impact of actuator faults on system performance by stabilizing the closed-loop system. In addition, the design of the fault reconstruction observer and the fault-tolerant controller is formulated in terms of linear matrix inequalities that can be conveniently solved using convex optimization techniques. Finally, simulation results on a truck-trailer system are presented to verify the effectiveness of the proposed approaches.
引用
收藏
页码:3885 / 3895
页数:11
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