Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights

Yuting Cao; Linhao Zhao; Qishui Zhong; Shiping Wen; Kaibo Shi; Jianying Xiao; Tingwen Huang

doi:10.1016/j.neunet.2023.03.032

Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights

Neural Netw. 2023 Jun:163:28-39. doi: 10.1016/j.neunet.2023.03.032. Epub 2023 Mar 27.

Authors

Yuting Cao¹, Linhao Zhao², Qishui Zhong³, Shiping Wen⁴, Kaibo Shi⁵, Jianying Xiao⁶, Tingwen Huang⁷

Affiliations

¹ School of Aeronautics and Astronautics, University of Electronic Science and Technology, Chengdu, 611731, China. Electronic address: caoyuting901@163.com.
² Australian AI Institute, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia. Electronic address: linhao.zhao@student.uts.edu.au.
³ School of Aeronautics and Astronautics, University of Electronic Science and Technology, Chengdu, 611731, China. Electronic address: zhongqs@uestc.edu.cn.
⁴ Australian AI Institute, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia. Electronic address: shiping.wen@uts.edu.au.
⁵ School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, 611040, China. Electronic address: skbs111@163.com.
⁶ School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, 611040, China. Electronic address: shawion1980@163.com.
⁷ Science Program, Texas A&M University at Qatar, Doha, 23874, Qatar. Electronic address: tingwen.huang@qatar.tamu.edu.

PMID: 37023543
DOI: 10.1016/j.neunet.2023.03.032

Abstract

This paper addresses fixed-time output synchronization problems for two types of complex dynamical networks with multi-weights (CDNMWs) by using two types of adaptive control methods. Firstly, complex dynamical networks with multiple state and output couplings are respectively presented. Secondly, several fixed-time output synchronization criteria for these two networks are formulated based on Lyapunov functional and inequality techniques. Thirdly, by employing two types of adaptive control methods, fixed-time output synchronization issues of these two networks are dealt with. At last, the analytical results are verified by two numerical simulations.

Keywords: Adaptive control; Complex dynamical networks; Fixed-time output synchronization; Multiple weights.

MeSH terms

Algorithms*
Neural Networks, Computer*
Time Factors