A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems With A Hybrid Event-Triggered Mechanism

Junfeng Zhang; Baozhu Du; Suhuan Zhang; Shihong Ding

doi:10.1109/JAS.2024.124677

Volume 11 Issue 11

Nov. 2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2024 > 11(11): 2298-2315

J. Zhang, B. Du, S. Zhang, and S. Ding, “A double sensitive fault detection filter for positive Markovian jump systems with a hybrid event-triggered mechanism,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 11, pp. 2298–2315, Nov. 2024. doi: 10.1109/JAS.2024.124677

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J. Zhang, B. Du, S. Zhang, and S. Ding, “A double sensitive fault detection filter for positive Markovian jump systems with a hybrid event-triggered mechanism,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 11, pp. 2298–2315, Nov. 2024. doi: 10.1109/JAS.2024.124677

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A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems With A Hybrid Event-Triggered Mechanism

doi: 10.1109/JAS.2024.124677

Funds: This work was supported by the National Natural Science Foundation of China (62073111, 62073167), the Natural Science Foundation of Hainan Province (621QN212), and Science Research Funding of Hainan University (KYQD(ZR)22180)

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Author Bio:
Junfeng Zhang (Senior Member IEEE) received the Ph.D. degree in control science and engineering from Shanghai Jiao Tong University in 2014. Now, he is a Professor at the School of Information and Communication Engineering, Hainan University. From December 2014 to May 2022, he worked in the School of Automation, Hangzhou Dianzi University. From August 2019 to August 2020, he visited Inria, University of Lille, France. His research interests include positive systems, switched systems, and model predictive control. He was the Co-Chair of Program Committee in the 6th International Conference on Positive Systems. He has published more than 50 journal and conference papers and one book in the field of positive systems

Baozhu Du received the B.S. degree in information and computing science, and the M.S. degree in operational research and cybernetics from Northeastern University in 2003 and 2006, respectively, the Ph.D. degree in mechanical engineering from The University of Hong Kong, China in 2010. From 2017 to 2019, she was an Alexander von Humboldt experienced Researcher in University of Duisburg-Essen, Germany. Now, she is a Professor in the School of Information and Communication Engineering, Hainan University. Her research interests include stability analysis and robust control/filter theory of time-delay systems, positive systems, Markovian jump systems, and networked control systems

Suhuan Zhang received the M.S. degree in control science and engineering from Hangzhou Dianzi University in 2022. She is currently a Ph.D. candidate in control science and engineering with the College of Electronics and Information Engineering, Tongji University. Her research interests include semi-Markovian (Markovian) jump systems, multi-agent systems, unknown input observer, and event-triggered control and filtering

Shihong Ding (Member IEEE) received the B.E. degree in mathematics from Anhui Normal University in 2004, and the M.S. and Ph.D. degrees in automatic control from Southeast University in 2007 and 2010, respectively. During the graduate studies, he visited The University of Texas at San Antonio, USA from August 2008 to August 2009. After graduation, he held a Research Fellowship with the University of Western Sydney, Australia for one year. He also visited Yeungnam University, South Korea, from July 2018 to August 2018 and RMIT University, Australia from December 2019 to February 2020, respectively. Since June 2010, he has been with the School of Electrical and Information Engineering, Jiangsu University, where he is currently a Full Professor. His research interests include sliding mode control and finite-time stability. He currently serves as a Subject Editor of Nonlinear Dynamics and an Associate Editor of International Journal of Adaptive Control and Signal Processing
Corresponding author: Baozhu Du, e-mail: baozhudu@hainanu.edu.cn
Received Date: 2024-04-24
Accepted Date: 2024-07-17

Abstract

Abstract

This paper is concerned with the double sensitive fault detection filter for positive Markovian jump systems. A new hybrid adaptive event-triggered mechanism is proposed by introducing a non-monotonic adaptive law. A linear adaptive event-triggered threshold is established by virtue of 1-norm inequality. Under such a triggering strategy, the original system can be transformed into an interval uncertain system. By using a stochastic copositive Lyapunov function, an asynchronous fault detection filter is designed for positive Markovian jump systems (PMJSs) in terms of linear programming. The presented filter satisfies both $ L_{-} $-gain ($ \ell_{-} $-gain) fault sensitivity and $ L_{1} $ ($ \ell_{1} $) internal differential privacy sensitivity. The proposed approach is also extended to the discrete-time case. Finally, two examples are provided to illustrate the effectiveness of the proposed design.
- Fault detection filter,
- hybrid event-triggered mechanism,
- positive Markovian jump systems (PMJSs),
- sensitivity

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References(45)

References

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A non-monotonic adaptive triggering law is established for PMJSs
Asynchronous filters with double sensitivity are proposed for PMJSs
A simple analysis and design approach is presented by combining stochastic co-positive Lyapunov function and linear programming

A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems With A Hybrid Event-Triggered Mechanism

doi: 10.1109/JAS.2024.124677

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