Finite-time synchronization of the complex dynamical network with non-derivative and derivative coupling

Xu, Yuhua; Zhou, Wuneng; Fang, Jian‐an; Xie, Chengrong; Tong, Dongbing

doi:10.1016/j.neucom.2015.09.008

Cited by 88 publications

(37 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Apart from modeling abrupt changes in systems, the Markov process can also be applied to the scope of digital core . In addition, many control methods for time‐delayed systems with Markovian jumping parameters have been proposed, including H ∞ control, adaptive control, dissipative control, finite‐time control, synchronization control, and asynchronous control …”

Section: Introductionmentioning

confidence: 99%

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Tong

Chen

et al. 2019

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

Summary The asynchronous control for the unified model of chaotic systems with Markovian jumping parameters is considered via the Takagi‐Sugeno (T‐S) fuzzy approach in this paper. According to jumping modes for chaotic systems and modes for the asynchronous controller, a double‐mode process is generated. By introducing the hidden Markov model (HMM), the asynchronization phenomenon is represented between the controller and chaotic systems. By linear matrix inequalities (LMIs), some conditions are received to guarantee the stochastic stability and the strict dissipativity for chaotic systems. Based on the stochastic stability theory and the dissipativity theory, the asynchronous controller is discussed. The proposed method can be applied to the mode‐independent controller and the synchronous controller. Finally, the effectiveness of the proposed controller is illustrated by two examples.

show abstract

Section: Introductionmentioning

confidence: 99%

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Tong

Chen

et al. 2019

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

show abstract

“…How to get * ? In this situation, finite-time problems of many systems have been attracting increasing interest [31][32][33][34][35][36][37][38][39][40][41][42]. For example, Liu et al [31] investigated finite/fixedtime synchronization of complex networks with stochastic disturbances.…”

Section: Introductionmentioning

confidence: 99%

Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

et al. 2019

Self Cite

View full text Add to dashboard Cite

This paper is mainly concerned with how nonlinear coupled one impacts synchronization dynamics of a class of nonlinear coupled Markovian switching multiweighted complex networks (NCMSMWCNs). Firstly, sufficient conditions of finite-time synchronization for a class of NCMSMWCNs and a class of linear coupled Markovian switching multiweighted complex networks (LCMSMWCNs) are investigated. Secondly, based on the derived results, how nonlinear coupled one affects synchronization dynamics of the NCMSMWCNs is analyzed from synchronization control rule. Thirdly, in order to further explore how nonlinear coupled one affects synchronization dynamics of the NCMSMWCNs, synchronization dynamics relationship of the NCMSMWCNs and the LCMSMWCNs is built. Furthermore, this relationship can also show how linear coupled one affects synchronization dynamics of the LCMSMWCNs. At last, numerical examples are provided to demonstrate the effectiveness of the obtained theory.

show abstract

“…Moreover, uncertainties exist widely in engineering and they often bring adverse effects to the stability and performance of real systems. So there is an increasing demand on developing better control techniques [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Synchronization of Uncertain Generalized Lorenz System by Adaptive Control

Zhou

2018

Journal of Control Science and Engineering

Self Cite

View full text Add to dashboard Cite

This paper investigates hybrid synchronization of the uncertain generalized Lorenz system. Several useful criteria are given for synchronization of two generalized Lorenz systems, and the adaptive control law and the parameter update law are used. In comparison with those of existing synchronization methods, hybrid synchronization includes full-order synchronization, reduced-order synchronization, and modified projective synchronization. What is more, control of the stability point, complete synchronization, and antisynchronization can coexist in the same system. Numerical simulations show the effectiveness of this method in a class of chaotic systems.

show abstract

Finite-time synchronization of the complex dynamical network with non-derivative and derivative coupling

Cited by 88 publications

References 28 publications

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Finite‐Time Synchronization and Synchronization Dynamics Analysis for Two Classes of Markovian Switching Multiweighted Complex Networks from Synchronization Control Rule Viewpoint

Hybrid Synchronization of Uncertain Generalized Lorenz System by Adaptive Control

Contact Info

Product

Resources

About