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Adaptive Event-triggered Fault Detection Filter for a Class of Conic-type Nonlinear Hidden Semi-Markov Jump Systems

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  • Control Theory and Applications
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Abstract

This paper investigates the filtering-based asynchronous fault detection problem for a class of continuous-time conic-type nonlinear semi-Markov jump systems via adaptive event-triggered approach. Firstly, the asynchrony of filter modes and system modes are described by a hidden semi-Markov model. Secondly, an adaptive event-triggered scheme is developed to reduce the transmissions from the system to the designed filter and improve the efficiency of data transmission. Then, by applying linear matrix inequalities techniques, sufficient conditions are obtained to ensure the stochastic stability and H∞ performance of the fault detection system. Finally, a tunnel diode circuit model is given to confirm the accuracy and effectiveness of the designed approach.

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Authors and Affiliations

  1. Anhui Engineering Laboratory of Human Robot Integration System and Intelligent Equipment, the School of Electrical Engineering and Automation, Anhui University, Hefei, 230601, China

    Kaixuan Chen, Xiang Zhang & Shuping He

  2. School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, 610106, China

    Kaibo Shi

  3. School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, Western Australia, 6102, Australia

    Yanyan Yin

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  1. Kaixuan Chen
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Correspondence to Shuping He.

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This work was supported in part by the Anhui Provincial Key Research and Development Project under Grant 2022i01020013, and the University Synergy Innovation Program of Anhui Province under Grant GXXT-2021-010.

Kaixuan Chen received his B.S. degree in automation from Anhui University, Hefei, China, in 2017. He is currently pursuing a Master’s degree in control engineering with the School of Electrical Engineering and Automation, Anhui University. His current research interests include stochastic control, and filtering and fault detection.

Xiang Zhang received his B.S. degree in electrical engineering and automation from Jiamusi University, Jiamusi, China, in 2019. He is currently pursuing a Master’s degree in control engineering with the School of Electrical Engineering and Automation, Anhui University, Hefei. His current research interests include stochastic control, sliding mode control, and filtering and fault detection.

Kaibo Shi was born in Anhui, China. He received his Ph.D. degree in instrumentation science and technology from the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China, in 2016. He is an Associate Professor with the School of Information Sciences and Engineering, Chengdu University, Chengdu. His current research interests include stability theorem, robustness stability, robust control, sampled-data control, synchronization, Lurie chaotic system, stochastic systems, and neural networks. Dr. Shi is a very active reviewer for many international journals.

Yanyan Yin received her B.Sc. degree in automation and an M.Sc. degree in control theory and control engineering from Jiangnan University, Wuxi, China, in 2007 and 2009, respectively, and a Ph.D. degree from the School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Australia, in 2013. She joined Jiangnan University as an Associate Professor in 2013. She is currently a Research Fellow with Curtin University. Her research interests include stochastic systems, complex systems control, and industrial system optimization.

Shuping He received his B.S. degree in automation and a Ph.D. degree in control theory and control engineering in Jiangnan University, Wuxi, China, in 2005 and 2011, respectively. From 2010 to 2011, he was a visiting scholar with the Control Systems Centre, the School of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK. He is now a Professor with the School of Electrical Engineering and Automation, Anhui University, Hefei, China. His current research interests include stochastic systems control, reinforcement learning, system modeling with applications, signal processing, and artificial intelligence methods. He has authored or co-authored more than 100 papers in professional journals, conference proceedings, and technical reports in the above areas and published two books about stochastic systems. He is also the associate or youth editor of many professional journals, such as IEEE/CAA Journal of Automatica Sinica, Journal of Central South University, etc.

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Chen, K., Zhang, X., Shi, K. et al. Adaptive Event-triggered Fault Detection Filter for a Class of Conic-type Nonlinear Hidden Semi-Markov Jump Systems. Int. J. Control Autom. Syst. 20, 3573–3583 (2022). https://doi.org/10.1007/s12555-021-0325-4

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