Adaptive Event-Triggered Fault Detection for Fuzzy Stochastic Systems With Missing Measurements

2018 ◽  
Vol 26 (4) ◽  
pp. 2201-2212 ◽  
Author(s):  
Zhaoke Ning ◽  
Jinyong Yu ◽  
Yingnan Pan ◽  
Hongyi Li
Keyword(s):  
Fault Detection ◽  
Stochastic Systems ◽  
Missing Measurements ◽  
Event Triggered

Event-triggered fault detection for linear stochastic systems

2017 ◽  
Vol 40 (12) ◽  
pp. 3449-3457
Author(s):  
Jinyong Yu ◽  
Zhaoke Ning ◽  
Yu Liu
Keyword(s):  
Fault Detection ◽  
Stochastic Systems ◽  
Detection Problem ◽  
Network Resources ◽  
Network Bandwidth ◽  
Filter Structure ◽  
Linear Stochastic Systems ◽  
The Mean ◽  
Release Strategy ◽  
Event Triggered

In this paper, the event-triggered fault-detection problem is investigated for Itô-type stochastic systems. A filter structure is used to construct a residual model for fault detection. For limited network resources, a novel event-triggered strategy is proposed, while a trigger condition is utilized to determine and transmit the useful data through the network. Compared with the traditional periodic release strategy, the proposed design approach can significantly reduce the utilization of network bandwidth. A new condition is proposed to achieve the mean-square asymptotical stability of the residual model with the desired fault-detection objective. A novel algorithm is derived to obtain the parameters of the filter and the event detector. Two simulation cases are provided to illustrate the effectiveness of the design strategy.

Event-triggered fault detection filter design for uncertain stochastic systems with package dropouts

2019 ◽  
Vol 233 (10) ◽  
pp. 1351-1360 ◽  
Author(s):  
Zhaoke Ning ◽  
Jinyong Yu ◽  
Tong Wang
Keyword(s):  
Fault Detection ◽  
Stochastic Systems ◽  
Filter Design ◽  
Network Resources ◽  
Design Algorithm ◽  
Fault Detection Filter ◽  
Filter Structure ◽  
Exponentially Stable ◽  
Detection Filter ◽  
Event Triggered

In this article, the event-triggered fault detection filter design problem is concerned with uncertain stochastic systems subject to package dropouts. First, a filter structure is constructed to achieve the desired fault detection objective. Second, an integrated model with an event-triggered scheme and a Bernoulli stochastic process are employed to save the limited network resources and describe the package dropouts phenomenon, which always appears in the real network environment. A new sufficient condition is provided to ensure that the obtained residual system is mean square robustly exponentially stable and satisfies the desired detection performance. Then, a novel co-design algorithm is derived to obtain the parameters of filter and event-triggered scheme. Finally, two simulation examples are provided to verify the effectiveness of the proposed design scheme.

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