scholarly journals Topology Detection for Output-Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Xinwei Wang ◽  
Guo-Ping Jiang ◽  
Chunxia Fan ◽  
Xu Wu
Keyword(s):  
Dynamical System ◽  
Numerical Simulations ◽  
Invariance Principle ◽  
Time Delays ◽  
Complex Dynamical Networks ◽  
Output Coupling ◽  
Complex Dynamical Network ◽  
Dynamical Networks ◽  
Transmission Delays ◽  
Response System

Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.

scholarly journals A New Model for Complex Dynamical Networks Considering Random Data Loss

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 797
Author(s):  
Xu Wu ◽  
Guo-Ping Jiang ◽  
Xinwei Wang
Keyword(s):  
Network Model ◽  
Network Models ◽  
Lyapunov Stability Theory ◽  
Complex Dynamical Networks ◽  
Output Coupling ◽  
Data Loss ◽  
Complex Dynamical Network ◽  
Dynamical Networks ◽  
Dynamical Network ◽  
Proposed Model

Model construction is a very fundamental and important issue in the field of complex dynamical networks. With the state-coupling complex dynamical network model proposed, many kinds of complex dynamical network models were introduced by considering various practical situations. In this paper, aiming at the data loss which may take place in the communication between any pair of directly connected nodes in a complex dynamical network, we propose a new discrete-time complex dynamical network model by constructing an auxiliary observer and choosing the observer states to compensate for the lost states in the coupling term. By employing Lyapunov stability theory and stochastic analysis, a sufficient condition is derived to guarantee the compensation values finally equal to the lost values, namely, the influence of data loss is finally eliminated in the proposed model. Moreover, we generalize the modeling method to output-coupling complex dynamical networks. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed model.

SYNCHRONIZATION INSIDE COMPLEX DYNAMICAL NETWORKS WITH DOUBLE TIME-DELAYS AND NONLINEAR INNER-COUPLING FUNCTIONS

2011 ◽  
Vol 25 (11) ◽  
pp. 1531-1541 ◽  
Author(s):  
WEIGANG SUN ◽  
YUEYING YANG ◽  
CHANGPIN LI ◽  
ZENGRONG LIU
Keyword(s):  
Vector Field ◽  
Complex Networks ◽  
Time Delays ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Numerical Examples ◽  
Theoretical Criterion ◽  
Double Time

In this article, synchronization inside complex networks with double time-delays and nonlinear inner-coupling functions are studied. Here double time-delays mean that each node vector field and every coupling node have retard time, while nonlinear inner-coupling functions refer to all the components of every node that are nonlinearly coupled. The theoretical criterion respecting synchronization is derived. And illustrative numerical examples are also given.

scholarly journals Finite-Time Synchronization of Complex Dynamical Networks with Nondelayed and Delayed Coupling by Continuous Function Controller

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xie Chengrong ◽  
Xing Yu ◽  
Xia Qing ◽  
Dongbing Tong ◽  
Yuhua Xu
Keyword(s):  
Continuous Function ◽  
Numerical Simulations ◽  
Finite Time ◽  
Time Synchronization ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Delayed Coupling ◽  
Special Case

This paper investigates the finite-time synchronization of complex dynamical networks with nondelayed and delayed coupling. By designing a simple continuous function controller, sufficient criteria for finite-time synchronization of dynamical networks with nondelayed and delayed coupling are obtained. As a special case, the continuous function controller designed in this paper may be the simplest and easy to implement for the finite-time synchronization of dynamical networks without delay. Finally, numerical simulations are given to verify the effectiveness of the conclusions presented in this paper.

scholarly journals Structural Balance Control of Complex Dynamical Networks Based on State Observer for Dynamic Connection Relationships

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zilin Gao ◽  
Yinhe Wang ◽  
Jiang Xiong ◽  
Yong Pan ◽  
Yuanyuan Huang
Keyword(s):  
Balance Control ◽  
Lyapunov Stability Theory ◽  
State Observer ◽  
The State ◽  
Complex Dynamical Networks ◽  
Complex Dynamical Network ◽  
Dynamical Networks ◽  
Structural Balance ◽  
Practical Applications ◽  
Coupled Subsystems

This paper investigates the observer-based structural balance control for a class of complex dynamical networks. Generally speaking, a complete complex dynamical network is composed of two coupled subsystems, which are called node subsystem (NS) and connection relationship subsystem (CS), respectively. Similar to synchronization and stabilization of networks, the structural balance is another phenomenon of networks and determined by the state of connection relationships. However, it is not feasible to design the controller for the CS directly because the states of the connection relationships are difficult to be measured accurately in practical applications. In order to solve this problem, a state observer for the CS has been designed. Thus, the structural balance controller in the CS can be directly designed by using the estimation information of the state observer. Then, with the help of the Lyapunov stability theory, it is proved that the CS can asymptotically track a given structural balance matrix under the influence of the observer-based controller. Finally, the results derived from this paper are demonstrated by performing a numerical example.

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