Dynamic-Event-Based Fault Detection for Markov Jump Systems Under Hidden-Markov Mode Observation-Reference-Cited by-同舟云学术

Dynamic-Event-Based Fault Detection for Markov Jump Systems Under Hidden-Markov Mode Observation

Published:2020-12-20 Issue:7 Volume:24 Page:917-924
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Xu Xiaoxiao,Wan Xiongbo, , ,

Abstract

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.

Funder

National Natural Science Foundation of China

Hubei Provincial Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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