Synchronisation control for neutral-type multi-slave stochastic hybrid systems

ABSTRACT

In this paper, an exponential synchronisation problem for neutral-type multi-slave hybrid systems with stochastic perturbation is discussed, where the adaptive synchronisation model involves a master system and multiple slave systems. By the use of generalised It$\widehat{o}$'s formula and M-matrix method, a sufficient condition is obtained to guarantee the stability of the error system, and the update law of the feedback controller is determined to deduce the synchronisation between the master system and the sum system of all slave systems. Finally, a numerical example is given to illustrate the effectiveness of the results obtained in this paper.

KEYWORDS:

• Multi-slave systems
• projective synchronisation
• M-matrix stochastic perturbation
• hybrid systems

Acknowledgments

The authors would like to thank the editors, the referees and Ms Sona Chahal very much for their help and useful suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is partially supported by the Natural Science Foundation of China [grant number 61573095]; the Natural Science Foundation of Shanghai [grant number 15ZR1401800 and 17ZR1400100]; Shanghai Municipal Education Commission and Shanghai Education Development Foundation [grant number 13CG29]; the Central Universities and DHU Distinguished Young Professor Program [grant number B201309]; the Chen Guang Project [grant number 13CG29].

Notes on contributors

Jun Zhou

Jun Zhou received his M.S. degree in computer application technology from Yunnan University, Yunnan, China, in 2010. Now he is under a Ph.D. candidate in control science and engineering from Donghua University, Shanghai and a teacher in Southwest Forestry University, Yunnan, China. His current research interests include neural networks, hybrid systems and complex networks.

Feng Pan

Feng Pan received his B.S. degree in computer science from Wuhan University, China, in 1998 and the Ph.D. degree in computer science from Shanghai Jiaotong University, China, in 2006. Now he is a lecturer in Donghua University, Shanghai, China. His current research interests include the wireless sensor networks and complex networks.

Tingting Cai

Tingting Cai received her B.S. degree from Yunnan Agricultural University, Kunming, China, in 2008, because her excellent behavior, she start to her master degree in 2009, and she start her Ph.D. research in 2011 without entrance examination because her excellent behavior, and obtained her Ph.D. degree in 2014. Now, her current research area is chemical ecology area.

Yuqing Sun

Yuqing Sun received her B.S. degrees and she is currently pursuing the Ph.D. degree in control science and engineering from Donghua University, Shanghai, China, in 2014. Her current research interests include synchronization and stability research of stochastic neural network systems and optimal control.

Wuneng Zhou

Wuneng Zhou received his B.S. degree in mathematics from Huazhong Normal University, China, in 1982 and the Ph.D. degree in control science and engineering from Zhejiang University, China, in 2005. Now he is a professor in Donghua University, Shanghai, China. His current research interests include the stability, the synchronization and control for neural networks, wireless sensor networks and complex networks.

Huashan Liu

Huashan Liu received his B.E. degree in Mechanical Engineering from Wuhan University, Wuhan, China, and the Ph.D. degree in Mechatronics from Zhejiang University, Hangzhou, China in 2005 and 2010, respectively. Since 2010, he has been with the College of Information Science and Technology, Donghua University, Shanghai, China, where he is currently an Associate Professor and Head of Department of Electrical and Electronic Engineering. During 2015-2016 he was a Visiting Professor with the Institute of Automatic Control Engineering (LSR), Technical University of Munich (TUM), Munich, Germany. His current research interests include nonlinear dynamics, robotics, mechatronics and motion control.