scholarly journals Pinning Adaptive Synchronization of Delayed Coupled Dynamical Networks via Periodically Intermittent Control

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Xueliang Liu ◽  
Shengbing Xu
Keyword(s):  
Lyapunov Method ◽  
Sufficient Conditions ◽  
Exponential Synchronization ◽  
Adaptive Synchronization ◽  
Intermittent Control ◽  
Dynamical Networks ◽  
Adaptive Feedback ◽  
Periodically Intermittent Control ◽  
Synchronization Problem ◽  
Theoretical Results

This paper investigates the exponential synchronization problem of delayed coupled dynamical networks by using adaptive pinning periodically intermittent control. Based on the Lyapunov method, by designing adaptive feedback controller, some sufficient conditions are presented to ensure the exponential synchronization of coupled dynamical networks with delayed coupling. Furthermore, a numerical example is given to demonstrate the validity of the theoretical results.

scholarly journals Exponential Synchronization of Inertial Cohen–Grossberg Neural Networks with Time-Varying Delays via Periodically Intermittent Control

2020 ◽  
Vol 15 (2) ◽  
pp. 15
Author(s):  
Qing Ding ◽  
Yinfang Song
Keyword(s):  
Neural Networks ◽  
Sufficient Conditions ◽  
Functional Method ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Time Varying ◽  
Periodically Intermittent Control ◽  
Synchronization Problem ◽  
Control Schemes ◽  
Inequality Techniques

This paper deals with the exponential synchronization problem of inertial Cohen–Grossberg neural networks with time-varying delays under periodically intermittent control. In light of Lyapunov–Krasovskii functional method and inequality techniques, some sufficient conditions are attained to ensure the exponential synchronization of the master-slave system on the basis of p-norm. Meanwhile, the periodically intermittent control schemes are designed. Finally, in order to verify the effectiveness of theoretical results, some numerical simulations are provided.

scholarly journals Semiglobal Finite-Time Synchronization of Complex Dynamical Networks via Periodically Intermittent Control

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yihan Fan ◽  
Hongmei Liu ◽  
Jun Mei
Keyword(s):  
Finite Time ◽  
Time Synchronization ◽  
Complex Dynamical Networks ◽  
Linear Matrix ◽  
Intermittent Control ◽  
Dynamical Networks ◽  
Periodically Intermittent Control ◽  
Finite Time Stability ◽  
Synchronization Problem ◽  
Theoretical Results

This paper studies the finite-time synchronization problem for a class of complex dynamical networks by means of periodically intermittent control. Based on some analysis techniques and finite-time stability theory, some novel and effective finite-time synchronization criteria are given in terms of a set of linear matrix inequalities. Particularly, the previous synchronization problem by using periodically intermittent control has been extended in this paper. Finally, numerical simulations are presented to verify the theoretical results.

scholarly journals Adaptive Aperiodically Intermittent Synchronization for Complex Dynamical Network with Unknown Time-Varying Outer Coupling Strengths

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Lihong Yan ◽  
Junmin Li
Keyword(s):  
Adaptive Learning ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Time Varying ◽  
Complex Dynamical Network ◽  
Dynamical Network ◽  
Synchronization Problem ◽  
Coupling Strengths ◽  
Inequality Techniques ◽  
Theoretical Results

In this paper, exponential synchronization problem of complex dynamical networks with unknown periodically coupling strengths was investigated. An aperiodically intermittent control synchronization strategy is proposed. Based on Lyapunov exponential stability theory, inequality techniques, and adaptive learning laws design, some sufficient exponential synchronization criteria for complex dynamical network with unknown periodical coupling weights are obtained. The numerical simulation example is presented to illustrate the feasibility of theoretical results.

scholarly journals Exponential Synchronization of Stochastic Complex Dynamical Networks with Impulsive Perturbations and Markovian Switching

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Wuneng Zhou ◽  
Anding Dai ◽  
Dongbing Tong ◽  
Jun Yang
Keyword(s):  
Stochastic Analysis ◽  
Function Method ◽  
Transition Probability ◽  
Sufficient Conditions ◽  
Exponential Synchronization ◽  
Markovian Switching ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Synchronization Problem ◽  
Lyapunov Function Method

This paper investigates the exponential synchronization problem of stochastic complex dynamical networks with impulsive perturbation and Markovian switching. The complex dynamical networks consist ofκmodes, and the networks switch from one mode to another according to a Markovian chain with known transition probability. Based on the Lyapunov function method and stochastic analysis, by employingM-matrix approach, some sufficient conditions are presented to ensure the exponential synchronization of stochastic complex dynamical networks with impulsive perturbation and Markovian switching, and the upper bound of impulsive gain is evaluated. At the end of this paper, two numerical examples are included to show the effectiveness of our results.

Exponential Synchronization of Stochastic Reaction-Diffusion Fuzzy Cohen-Grossberg Neural Networks With Time-Varying Delays Via Periodically Intermittent Control

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Qintao Gan ◽  
Yang Li
Keyword(s):  
Neural Networks ◽  
Sufficient Conditions ◽  
Reaction Diffusion ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Time Varying ◽  
Synchronization Problem ◽  
Diffusion Effects ◽  
Stochastic Reaction ◽  
Delay Partitioning

In this paper, the exponential synchronization problem for fuzzy Cohen-Grossberg neural networks with time-varying delays, stochastic noise disturbance, and reaction-diffusion effects are investigated. By introducing a novel Lyapunov-Krasovskii functional with the idea of delay partitioning, a periodically intermittent controller is developed to derive sufficient conditions ensuring the addressed neural networks to be exponentially synchronized in terms of p-norm. The results extend and improve upon earlier work. A numerical example is provided to show the effectiveness of the proposed theories.

scholarly journals Adaptive Impulsive Observer for Outer Synchronization of Delayed Complex Dynamical Networks with Output Coupling

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Song Zheng
Keyword(s):  
Control Method ◽  
Hybrid Control ◽  
Sufficient Conditions ◽  
Complex Dynamical Networks ◽  
Output Coupling ◽  
Lyapunov Stability Theorem ◽  
Dynamical Networks ◽  
Synchronization Problem ◽  
Control Schemes ◽  
Theoretical Results

The synchronization problem of two delayed complex dynamical networks with output coupling is investigated by using impulsive hybrid control schemes, where only scalar signals need to be transmitted from the drive network to the response one. Based on the Lyapunov stability theorem and the impulsive hybrid control method, some sufficient conditions guaranteeing synchronization of such complex networks are established for both the cases of coupling delay and node delay are considered, respectively. Finally, two illustrative examples with numerical simulations are given to show the feasibility and efficiency of theoretical results.

scholarly journals Alternate Event-triggered Aperiodically Intermittent Control for Synchronization of Multi-weighted Complex Networks

2021 ◽  
Author(s):  
Dongsheng Xu ◽  
Huan Su ◽  
Chenfei Guo
Keyword(s):  
Complex Networks ◽  
Sufficient Conditions ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Real Time Control ◽  
Practical Applications ◽  
Time Control ◽  
Theoretical Results ◽  
Event Triggered ◽  
Weighted Complex Networks

Abstract In this paper, the exponential synchronization problem for multi-weighted complex networks via alternate event-triggered aperiodically intermittent control (AETAIC) is considered. Different from existing literature, the proposed AETAIC is triggered alternatively by two pre-defined conditions, which can fast react to asynchronous external events and show better real-time control performance. Meanwhile, AETAIC removes the restrictions of traditional intermittent control on the lower bound of control intervals and upper bound of control periods or the maximum proportion of rest intervals. Though graph theory and Lyapunov method, several sufficient conditions are given to ensure exponential synchronization of the studied networks and Zeno behaviors can be excluded. Moreover, the theoretical results demonstrate that the control gain affects the control widths and exponential convergence rate, which shows that AETAIC can further reduce the frequency of controller updates and release the computation burdens. Finally, in order to illustrate the theoretical results, two practical applications about Chua's circuits and coupled oscillators are presented. Meanwhile, numerical simulations are provided to validate the effectiveness of the results.

Periodically intermittent control for synchronized stationary distribution and synchronization of memristor-based stochastic coupled systems

2019 ◽  
Vol 41 (14) ◽  
pp. 4142-4156
Author(s):  
Yan Liu ◽  
Wenxue Li ◽  
Kaiwen Feng ◽  
Huihui Song
Keyword(s):  
Stationary Distribution ◽  
Control Strategy ◽  
Coupled Oscillators ◽  
Lyapunov Method ◽  
Coupled Systems ◽  
Intermittent Control ◽  
Periodically Intermittent Control ◽  
A New Technique ◽  
First Time ◽  
Theoretical Results

This article is concerned with inner synchronized stationary distribution for memristor-based stochastic coupled systems for the first time. It is worth mentioning that periodically intermittent control that serves as a new technique is introduced into the investigation of synchronized stationary distribution. Based on the graph theory, the Lyapunov method and periodically intermittent control strategy, two main theorems that guarantee the existence of a synchronized stationary distribution are obtained, whose results illustrate that the existing region of synchronized stationary distribution depends on the control rate, coupled strength and so on. On the other hand, exponential synchronization is also taken into consideration and a theorem is presented. In addition, as applications, memristor-based stochastic coupled oscillators and stochastic coupled Chua’s circuits are presented to verify the practicability of theoretical results. Finally, two simulation examples are given to demonstrate the effectiveness and feasibility of theoretical results.

scholarly journals Adaptive Exponential Synchronization for Stochastic Competitive Neural Networks with Time-Varying Leakage Delays and Reaction-Diffusion Terms

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
Zhiqiang Wang ◽  
Lili Wang ◽  
Rui Xu
Keyword(s):  
Neural Networks ◽  
Reaction Diffusion ◽  
Diffusion Time ◽  
Exponential Synchronization ◽  
Spatial Diffusion ◽  
Time Varying ◽  
Adaptive Feedback ◽  
Leakage Delays ◽  
Synchronization Problem ◽  
Theoretical Results

We study the exponential synchronization problem for a class of stochastic competitive neural networks with different timescales, as well as spatial diffusion, time-varying leakage delays, and discrete and distributed time-varying delays. By introducing several important inequalities and using Lyapunov functional technique, an adaptive feedback controller is designed to realize the exponential synchronization for the proposed competitive neural networks in terms of p-norm. According to the theoretical results obtained in this paper, the influences of the timescale, external stimulus constants, disposable scaling constants, and controller parameters on synchronization are analyzed. Numerical simulations are presented to show the feasibility of the theoretical results.

Sign in / Sign up

Export Citation Format

Share Document