Fuzzy Fault Detection for Markov Jump Systems With Partly Accessible Hidden Information: An Event-Triggered Approach

2021 ◽  
pp. 1-10
Author(s):  
Peng Cheng ◽  
Shuping He ◽  
Vladimir Stojanovic ◽  
Xiaoli Luan ◽  
Fei Liu
Author(s):  
Xiaoxiao Xu ◽  
Xiongbo Wan ◽  
◽  
◽  

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.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 248-258
Author(s):  
Wenqian Xie ◽  
Yong Zeng ◽  
Kaibo Shi ◽  
Xin Wang ◽  
Qianhua Fu

2021 ◽  
pp. 1-12
Author(s):  
Peng Cheng ◽  
Hai Wang ◽  
Vladimir Stojanovic ◽  
Shuping He ◽  
Kaibo Shi ◽  
...  

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