Robust fault estimation based on learning observer for Takagi‐Sugeno fuzzy systems with interval time‐varying delay

Summary This paper studies the problem of robust fault estimation for a class of Takagi‐Sugeno(T‐S) fuzzy systems which subject to interval time‐varying delay, external disturbance, and actuator fault. The designed learning observer can achieve simultaneous estimation of system state and time‐varyin...

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Veröffentlicht in:International journal of adaptive control and signal processing 2020-01, Vol.34 (1), p.92-109
Hauptverfasser: You, Fuqiang, Cheng, Shiya, Tian, Kuo, Zhang, Xinyan
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Sprache:eng
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Zusammenfassung:Summary This paper studies the problem of robust fault estimation for a class of Takagi‐Sugeno(T‐S) fuzzy systems which subject to interval time‐varying delay, external disturbance, and actuator fault. The designed learning observer can achieve simultaneous estimation of system state and time‐varying or constant actuator fault. Then, we construct a new Lyapunov‐Krasovskii functional including the information of the lower and upper delay bounds; compared with the time‐varying delay, the interval time‐varying delay is the less conservative form. Furthermore, one less conservative delay‐dependent condition for the existence of learning observer is given in terms of linear matrix inequalities. In addition, the results for the systems with interval time‐varying delay are simplified when the delay is not concluded. Finally, simulation results of two examples are presented to show the effectiveness of the proposed method.
ISSN:0890-6327
1099-1115
DOI:10.1002/acs.3070