Anti-windup compensation design for a class of distributed time-delayed cellular neural networks

doi:10.21629/JSEE.2019.06.15

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (6): 1212-1223.doi: 10.21629/JSEE.2019.06.15

• Control Theory and Application • Previous Articles Next Articles

Anti-windup compensation design for a class of distributed time-delayed cellular neural networks

Hanlin HE¹(), Miao ZHA^1,*(), Shaofeng BIAN²()

¹ Department of Basic Courses, Naval University of Engineering, Wuhan 430033, China
² Department of Navigation Engineering, Naval University of Engineering, Wuhan 430033, China

Received:2019-01-10 Online:2019-12-20 Published:2019-12-25
Contact: Miao ZHA E-mail:hanlinhe62@aliyun.com;zha30@qq.com;sfbian@sina.com
About author:HE Hanlin was born in 1962. He received his B.S. degree in mathematics from Central China Normal University, Wuhan, China, in 1983. He received his M.S. degree in applied mathematics from Chongqing University, Chongqing, China, in 1989, and his Ph.D. degree in control science and engineering from Huazhong University of Science and Technology, Wuhan, China, in 2003. From 1990 to 1999, he was a lecturer with Naval University of Engineering. From 2001 to 2005, he was an associate professor. Since 2006, he has been a professor with the Department of Basic Courses, Naval University of Engineering. His research interests include feedback control, fuzzy control, cellular neural networks control, anti-windup control, nonlinear systems, Lurie systems, chaos control and synchronization. E-mail: hanlinhe62@aliyun.com|ZHA Miao was born in 1991. She received her B.S. degree in electronic information engineering from China University of Geosciences, Wuhan, China, in 2013 and M.S. degree in communication and information system from Naval University of Engineering, Wuhan, China, in 2015. She is currently pursuing her Ph.D. degree in control science and engineering at Naval University of Engineering, Wuhan, China. Her research interests include feedback control, anti-windup control, and nonlinear systems. E-mail: zha30@qq.com|BIAN Shaofeng was born in 1961. He received his B.S. degree in geodesy and M.S. degree in astronomical geodesy in Institute of Surveying and Mapping, the PLA Information Engineering University, Zhengzhou, China, in 1982 and 1985, respectively and Ph.D. degree from Wuhan Technical University of Surveying and Mapping in 1992. He is a professor in the Department of Navigation Engineering, Naval University of Engineering. He was awarded an Alexander von Humboldt Research Fellowship in 1996. He got funded by the National Science Foundation for Distinguished Young Scholars, in 2001. His research interests include satellite navigation and geodesy. E-mail: sfbian@sina.com
Supported by:
the National Natural Science Foundation of China(61374003);the National Natural Science Foundation of China(41631072);the Academic Foundation of Naval University of Engineering(20161475);This work was supported by the National Natural Science Foundation of China (61374003; 41631072) and the Academic Foundation of Naval University of Engineering (20161475)

Abstract

Abstract:

Both time-delays and anti-windup (AW) problems are conventional problems in system design, which are scarcely discussed in cellular neural networks (CNNs). This paper discusses stabilization for a class of distributed time-delayed CNNs with input saturation. Based on the Lyapunov theory and the Schur complement principle, a bilinear matrix inequality (BMI) criterion is designed to stabilize the system with input saturation. By matrix congruent transformation, the BMI control criterion can be changed into linear matrix inequality (LMI) criterion, then it can be easily solved by the computer. It is a one-step AW strategy that the feedback compensator and the AW compensator can be determined simultaneously. The attraction domain and its optimization are also discussed. The structure of CNNs with both constant timedelays and distribute time-delays is more general. This method is simple and systematic, allowing dealing with a large class of such systems whose excitation satisfies the Lipschitz condition. The simulation results verify the effectiveness and feasibility of the proposed method.

CLC Number:

Hanlin HE, Miao ZHA, Shaofeng BIAN. Anti-windup compensation design for a class of distributed time-delayed cellular neural networks[J]. Journal of Systems Engineering and Electronics, 2019, 30(6): 1212-1223.

Figures/Tables 8

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Anti-windup compensation design for a class of distributed time-delayed cellular neural networks

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