scholarly journals Adaptive Finite-Time Synchronization Control for Teleoperation System With Varying Time Delays

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 40940-40949 ◽  
Author(s):  
Haochen Zhang ◽  
Aiguo Song ◽  
Shaobo Shen
Keyword(s):  
Finite Time ◽  
Time Delays ◽  
Time Synchronization ◽  
Synchronization Control ◽  
Teleoperation System

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

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Bin Yang ◽  
Xin Wang ◽  
Yongju Zhang ◽  
Yuhua Xu ◽  
Wuneng Zhou
Keyword(s):  
Complex Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Markovian Switching ◽  
Synchronization Control ◽  
Dynamics Analysis ◽  
Numerical Examples ◽  
Control Rule ◽  
Relationship Of

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.

scholarly journals Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ziye Zhang ◽  
Xiaoping Liu ◽  
Chong Lin ◽  
Bing Chen
Keyword(s):  
Neural Networks ◽  
Lyapunov Function ◽  
Recurrent Neural Networks ◽  
Finite Time ◽  
Time Delays ◽  
Time Synchronization ◽  
Great Difficulty ◽  
Activation Functions ◽  
Complex Valued ◽  
Independent Parameters

This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.

Finite-time synchronization of memristor-based complex-valued neural networks with time delays

2019 ◽  
Vol 383 (19) ◽  
pp. 2255-2263 ◽  
Author(s):  
Kaili Sun ◽  
Song Zhu ◽  
Yongchang Wei ◽  
Xiaoke Zhang ◽  
Fei Gao
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Delays ◽  
Time Synchronization ◽  
Complex Valued
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