Interval observer-based fault detection in finite frequency domain for discrete-time fuzzy systems

被引:22
|
作者
Zhang, Zhi-Hui [1 ]
Yang, Guang-Hong [1 ,2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Discrete-time fuzzy systems; Fault detection; Interval observers; Piecewise Lyapunov functions; Finite frequency domain; NONLINEAR-SYSTEMS; FEEDBACK CONTROL; DETECTION FILTER; DESIGN; THRESHOLD; DIAGNOSIS; STABILIZATION; STABILITY; DELAY;
D O I
10.1016/j.neucom.2018.05.020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a new method for detecting faults in discrete-time fuzzy systems. First, the piecewise interval observers are constructed based on the output-space partition technique. Second, l(1) performance is introduced to attenuate the persistent bounded disturbances and H_ performance in finite frequency domain is employed to improve fault sensitivity of the residual intervals. Then, the observer gains can be determined by solving the disturbance attenuation, fault sensitivity and non-negativity conditions, simultaneously. Different from the classical fault detection methods with residual evaluation functions and threshold generators, the proposed interval observers are able to generate the natural thresholds. Finally, the developed technique is demonstrated in a simulation example. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:38 / 45
页数:8
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