Volume 31, Issue 18 pp. 9562-9587
RESEARCH ARTICLE

Finite-time fault detection for multiple delayed semi-Markovian jump random systems

Shaoxin Sun

Shaoxin Sun

College of Automation, Chongqing University, Chongqing, China

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Xin Dai

Corresponding Author

Xin Dai

College of Automation, Chongqing University, Chongqing, China

Correspondence Xin Dai, College of Automation, Chongqing University, Chongqing, 400044, China.

Email: [email protected]

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Liu Yang

Liu Yang

College of Information Science and Engineering, Northeastern University, Shenyang, China

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Juan Zhang

Juan Zhang

College of Information Science and Engineering, Northeastern University, Shenyang, China

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Xiangpeng Xie

Xiangpeng Xie

Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China

School of Information Science and Engineering, Chengdu University, Chengdu, China

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First published: 01 October 2021
Citations: 6

Funding information: National Natural Science Foundation of China, 62003061; 51777022; 62022044; 62103066; The third batch of special grants of China Postdoctoral Science Foundation, 2021TQ0392; Jiangsu Natural Science Foundation for Distinguished Young Scholars, BK20190039

Abstract

This work focuses on the problem of finite-time multiple delay-dependent filter-based fault detection (FD) and fault-tolerant control (FTC) for semi-Markovian jump random nonlinear systems subject to state and input constraints. There are model uncertainties, multiple time-varying delays, nonlinear dynamics as well as faults in these systems. This study is the first time to try. In addition, this article both considers stochastic finite-time boundedness and input–output finite-time mean square stabilization. A semi-Markovian jump filter, a semi-Markovian jump controller and a fault weighting system are developed to achieve FD and FTC. Then, an augmented closed-loop nonlinear system can be established. Moreover, multiple delay-dependent sufficient conditions are produced by means of stochastic Lyapunov function in this framework of linear matrix inequalities. Finally, an example is shown to bring out the effectiveness of the method addressed in this study.

CONFLICT OF INTEREST

The authors declared that they have no conflict of interest to this work.

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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