scholarly journals Pinning Synchronization of Nonlinearly Coupled Complex Dynamical Networks on Time Scales

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fang-Di Kong
Keyword(s):  
Time Scales ◽  
Discrete Time ◽  
Control Strategy ◽  
Continuous Time ◽  
General Framework ◽  
Pinning Control ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Numerical Examples ◽  
Synchronization Problem

In this paper, we study the synchronization problem for nonlinearly coupled complex dynamical networks on time scales. To achieve synchronization for nonlinearly coupled complex dynamical networks on time scales, a pinning control strategy is designed. Some pinning synchronization criteria are established for nonlinearly coupled complex dynamical networks on time scales, which guarantee the whole network can be pinned to some desired state. The model investigated in this paper generalizes the continuous-time and discrete-time nonlinearly coupled complex dynamical networks to a unique and general framework. Moreover, two numerical examples are given for illustration and verification of the obtained results.

scholarly journals Synchronization of Complex Dynamical Networks on Time Scales via Pinning Control

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fang-Di Kong ◽  
Jian-Ping Sun
Keyword(s):  
Time Scales ◽  
Pinning Control ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Numerical Example ◽  
Synchronization Problem

In this paper, we are concerned with the synchronization problem of complex dynamical networks on time scales. Some pinning synchronization criteria, which combine main characteristics of time scales with main parameters of the pinning controlled network, are established. A numerical example is also included to verify the effectiveness of the results obtained.

Synchronization control of complex dynamical networks with piecewise constant arguments

2018 ◽  
Vol 41 (2) ◽  
pp. 540-551 ◽  
Author(s):  
Tianhu Yu ◽  
Menglong Su
Keyword(s):  
Impulsive Control ◽  
Lyapunov Stability Theory ◽  
Pinning Control ◽  
Complex Dynamical Networks ◽  
Control Law ◽  
Dynamical Networks ◽  
Piecewise Constant Arguments ◽  
Piecewise Constant ◽  
Synchronization Problem ◽  
Theoretical Results

The pinning synchronization problem is investigated for complex dynamical networks with hybrid coupling via impulsive control. Based on the Lyapunov stability theory, some novel synchronization criteria are derived and an impulsive pinning control law is proposed. By introducing a differential inequality for systems with piecewise constant arguments, it is not necessary to establish any relationship between the norms of the error states with or without piecewise constant arguments. Typical numerical examples are utilized to illustrate the validity and improvements as regards conservativeness of the theoretical results.

scholarly journals On Hybrid Adaptive and Pinning Consensus for Multiagent Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lianghao Ji ◽  
Yi Tang ◽  
Qun Liu
Keyword(s):  
Convergence Rate ◽  
Discrete Time ◽  
Continuous Time ◽  
Spanning Tree ◽  
Pinning Control ◽  
Control Laws ◽  
Numerical Examples ◽  
Multiagent Networks ◽  
Directed Spanning Tree ◽  
Pinning Scheme

The consensus problems for both continuous-time and discrete-time multiagent networks are deeply investigated by adopting hybrid adaptive and pinning control laws, respectively. Particularly, the topology of the networks needs to neither be symmetric nor contain a directed spanning tree and some useful criteria are addressed analytically. Simultaneously, a comprehensive pinning scheme is proposed as well which shows that the nodes with zero in-degree need to be pinned primarily in order to guarantee the system to achieve consensus, and then the nodes whose out-degrees are bigger than their in-degrees can give priority to be pinned compared to other nodes for improving the convergence rate of the system, whereas it is also interesting to find out that the regular rule does not always hold, that is, the more nodes are selected to be pinned, the faster the system will converge. Finally, the validity of our theoretical findings is verified by several numerical examples.

scholarly journals Neural network based asynchronous synchronization for fuzzy hidden Markov jump complex dynamical networks

2021 ◽  
Author(s):  
Chao Ma ◽  
Liziyi Hao ◽  
Hang Fu
Keyword(s):  
Neural Network ◽  
Hidden Markov ◽  
Sufficient Conditions ◽  
Complex Dynamical Networks ◽  
Linear Matrix ◽  
Markov Jump ◽  
Dynamical Networks ◽  
Synchronization Problem ◽  
The Neural Network ◽  
Takagi Sugeno

AbstractThis paper investigates the drive-response synchronization problem of Takagi–Sugeno fuzzy hidden Markov jump complex dynamical networks. More precisely, a novel asynchronous synchronization control strategy is developed for coping with mismatched hidden jumping modes. Furthermore, the neural network is adopted with online learning laws for unknown function approximation. By taking advantage of Lyapunov method, sufficient conditions are established to ensure mean-square synchronization performance with disturbances. Based on the synchronization criterion, asynchronous controller gains are designed in terms of linear matrix inequalities. An illustrative example is finally given to validate the effectiveness of the proposed synchronization techniques.

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