Finite-Time Synchronization and Identification between Two Nonlinear Coupled Multiweighted Markovian Switching Delayed Networks with Uncertain Models and External Disturbances

Xiaofei Chen,Haifeng Qiu,Chong Xu,Zhipeng Sun

doi:10.1155/2020/6620515

Xiaofei Chen, Haifeng Qiu + Show 2 more

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https://doi.org/10.1155/2020/6620515

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In this paper, two different nonlinear coupled Markovian switching delayed network models with multiple weights are established, and the effects of parameter and model uncertainties and external disturbances are fully considered. Firstly, based on the finite-time theory, several sufficient conditions for the finite-time synchronization of Markovian switching networks are obtained. Secondly, under the feedback controller with adaptive laws, when the synchronization of the networks is achieved in a finite time, the uncertain parameters of the networks can also be identified as true values. Finally, a representative numerical simulation is given to further illustrate the validity and practicability of the theoretical analysis and proof of this paper.

Highlights

In the real world, the coupling relationship of Markovian switching networks cannot be all linear, and nonlinear coupling systems are more common
In [14], the authors concerned with the problem of synchronization in nonlinear complex networks with multiple time-varying delays via adaptive aperiodic intermittent control
In the actual signal transmission process, time delays are often caused by factors, such as transmission speed limitations, network information congestion, and the influence of the transmission environment [15, 16]. us, considering the above reasons, time delays should be considered in the synchronization of Markovian switching complex networks

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Introduction

The coupling relationship of Markovian switching networks cannot be all linear, and nonlinear coupling systems are more common. Based on the above discussion, this paper mainly studied the finite-time synchronization and identification problems of nonlinear coupled Markovian switching delayed networks with multiple weights, in presence of uncertain parameters, uncertain model, and external disturbances on the networks.

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