Dynamic-Event-Based Fault Detection for Markov Jump Systems Under Hidden-Markov Mode Observation
Xiaoxiao Xu*,**,*** and Xiongbo Wan*,**,***,
*School of Automation, China University of Geosciences
No. 388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China
**Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
Wuhan, Hubei 430074, China
***Engineering Research Center of Intelligent Technology for Ger-Exploration, Ministry of Education
Wuhan, Hubei 430074, China
The fault detection (FD) problem is investigated for event-triggered discrete-time Markov jump systems (MJSs) with hidden-Markov mode observation. A dynamic-event-triggered mechanism, which includes some existing ones as special cases, is proposed to reduce unnecessary data transmissions to save network resources. Mode observation of the MJS by the FD filter (FDF) is governed by a hidden Markov process. By constructing a Markov-mode-dependent Lyapunov function, a sufficient condition in terms of linear matrix inequalities (LMIs) is obtained under which the filtering error system of the FD is stochastically stable with a prescribed H∞ performance index. The parameters of the FDF are explicitly given when these LMIs have feasible solutions. The effectiveness of the FD method is demonstrated by two numerical examples.
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