Finite-time synchronisation for periodic delayed master-slave neural networks with weighted try-once-discard protocol

Abstract

This paper focuses on the finite-time (FT) synchronisation for master-slave periodic neural networks (NNs) with mixed time-varying delays. In order to make full use of the limited network bandwidth caused by sensor energy constraint, a transmission channel assignment method is established, and a weighted try-once-discard (WTOD) protocol is employed for each channel. A WTOD protocol-dependent periodic controller is designed to ensure that the slave periodic NNs can synchronise with the master one. Based on a periodic Lyapunov–Krasovskii function, sufficient conditions are established to guarantee that the synchronisation error system is FT bounded. Finally, a numerical example is presented to demonstrate the validity of the theoretical results.

Keywords:

• Periodic neural networks
• finite-time synchronisation
• mixed delays
• weighted try-once-discard protocol

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant Numbers (62006043, 61875040, 61903093), the Local Innovative and Research Teams Project of Guangdong Special Support Program (2019BT02X353), and the Innovative Research Team Program of Guangdong Province Science Foundation (2018B030312006).

Notes on contributors

Chang Liu

Chang Liu was born in Xiangcheng, China, in 1992. He received the B.S. degree from Henan University, Kaifeng, China, in 2016, and the M.S. degree in control science and engineering from the Guangdong University of Technology, Guangzhou, China, in 2019, where he is currently pursuing the Ph.D. degree in control science and engineering.

Jie Li

Jie Li was born in Xinxiang, China, in 1997. She received the B.S. degree from the School of Electrical Engineering and Automation, Henan Institute of Technology, Xinxiang, Henan, China, in 2020. She is currently pursuing the M.S. degree in control science and engineering with the Guangdong University of Technology, Guangzhou, China.

Ming Lin

Ming Lin was born in Guangdong Province, China, in 1976. He received the B.S. degree in applied electronic technology from Beijing University of Posts and Telecommunications, Beijing, China, in 1999, the M.S. degree in Optics from Beijing University of Posts and Telecommunications, Beijing, China, in 2002, and the Ph.D. degree in Optical engineering from Beijing University of Posts and Telecommunications, Beijing, China, in 2016. He worked in Guangdong Telecom Planning and Design Institute Co., Ltd. From May 2002 to December 2019. Now he is an associate professor with School of Automation, at Guangdong University of Technology, Guangzhou, China. His research interests include High-speed optical communication, networked control systems, 5G applications.

Yanling Yang

Yanling Yang was born in HeNan Province, China, in 1979. She received the B.S. degree from ChongQing Post and Telecommunication University, ChongQing, China, in 2000, the M.S. degree from ChongQing Post and Telecommunication University, ChongQing, China, in 2004. Now she is a associate professor with School of Information Technology, Guangdong Industry Polytechnic, Guangzhou, China. Her research interests include network engineering and control systems.

Hongxia Rao

Hongxia Rao was born in Jiangsu Province, China, in 1986. She received the B.S. degree from Nanchang Hangkong University, Nanchang, China, in 2007, the M.S. degree from Nanjing University of Science and Technology, NanJing, China, in 2009, and the Ph.D. degree in control science and engineering from Guangdong University of Technology, China, in 2019. Now she is a lecturer with School of Automation, at Guangdong University of Technology, Guangzhou, China. Her research interests include networked control systems, Markov jump systems and neural networks.