Stochastic stability analysis of integral non-homogeneous Markov jump systems

ABSTRACT

This paper investigates the problem of stability analysis for time-delay integral Markov jump systems with time-varying transition rates. Some free-weight matrices are addressed and sufficient conditions are established under which the system is stochastically stable. The bound of delay is larger than those in other results obtained, which guarantees that the proposed conditions are tighter. Numerical examples show the effectiveness of the method proposed.

KEYWORDS:

• Markov jump systems
• time delay
• non-homogeneous jump
• nonlinear

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work has been partially supported by National Natural Science Foundation of PR China [grant number 61503155], [grant number 61773011]; Fundamental Research Funds for the Central Universities of China [grant number JUSRP51407B].

Notes on contributors

Yanyan Yin

Yanyan Yin received the B.Sc. degree in automation and the M.Sc. degree in control theory and control engineering from Jiangnan University, Wuxi, China, in 2007 and 2009, respectively, and she received Ph.D. degree in the school of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Australia in 2013. She joined in Jiangnan University in 2013 as an associate professor, and now she is a research fellow Curtin University. Her research interests include stochastic systems, complex nonlinear systems and optimization.

Lijie Zhu

Lijie Zhu received the B.S. degree from Jiangnan University, China, in 2015. He is currently pursuing the M.S. degree in control science and engineering from Jiangnan University, Wuxi, China. His research interest focuses on the control of stochastic systems.

Hongbing Zeng

Hongbing Zeng received the B.Sc. degree in electrical engineering from Tianjin University of Technology and Education, Tianjin, China, in 2003, M.Sc. degree in computer science from Central South University of Forestry, Changsha, China, in 2006, and Ph.D. degree in control science and engineering from Central South University, Changsha, China, in 2012. Since July 2003, he has been with the Department of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou, China, where he is currently an associate professor of automatic control engineering. From September 2013 to August 2014, he was a Postdoctoral Research Associate in the Department of Electrical Engineering, Yeungnam University, Kyongsan, Korea. His current research interests are time-delay systems, neural networks and networked control systems.

Yanqing Liu

Yanqing Liu received Ph.D. degree from Curtin University, Australia. He joined in Jiangnan University, Wuxi, China in 2015 as an associate professor. His research interests include stochastic optimization and hybrid system control, predictive control and complex nonlinear systems.

Fei Liu

Fei Liu received the Ph.D. degree in control science and control engineering from Zhejiang University, Hangzhou, China. He is currently a Professor with the Institute of Automation, Jiangnan University, Wuxi, China. His research interests include advanced control theory and applications, batch process control engineering, statistical monitoring and diagnosis in industrial processes, and intelligent techniques with emphasis on fuzzy and neural systems.