Dynamical Analysis and Synchronization of Complex Network Dynamic Systems under Continuous-Time

Author:

Yang Rui1,Tian Huaigu12ORCID,Wang Zhen3ORCID,Wang Wei1,Zhang Yang1

Affiliation:

1. Xi’an Key Laboratory of Human-Machine Integration and Control Technology for Intelligent Rehabilitation, Xijing University, Xi’an 710123, China

2. Shaanxi International Joint Research Center for Applied Technology of Controllable Neutron Source, Xijing University, Xi’an 710123, China

3. School of Mathematics and Computer Science, Yan’an University, Yan’an 716000, China

Abstract

In multilayer complex networks, the uncertainty in node states leads to intricate behaviors. It is, therefore, of great importance to be able to estimate the states of target nodes in these systems, both for theoretical advancements and practical applications. This paper introduces a state observer-based approach for the state estimation of such networks, focusing specifically on a class of complex dynamic networks with nodes that correspond one-to-one. Initially, a chaotic system is employed to model the dynamics of each node and highlight the essential state components for analysis and derivation. A network state observer is then constructed using a unique diagonal matrix, which underpins the driver and response-layer networks. By integrating control theory and stability function analysis, the effectiveness of the observer in achieving synchronization between complex dynamic networks and target systems is confirmed. Additionally, the efficacy and precision of the proposed method are validated through simulation.

Funder

Scientific Research Program Funded by Education Department of Shaanxi Provincial Government

Scientific Research Foundation of Xijing University

Horizontal Project

National Natural Science Foundation of China

Fund of the Science and Technology Innovation Team of Shaanxi

Natural Science Basic Research Program of Shaanxi

Support Plan for Sanqin Scholars Innovation Team in Shaanxi Province of China

Fund of the Youth Innovation Team of Shaanxi Universities

Publisher

MDPI AG

Reference47 articles.

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