Dynamic Self-Triggered Impulsive Synchronization of Complex Networks With Mismatched Parameters and Distributed Delay

Synchronization of complex networks with nonlinear couplings and distributed time-varying delays is investigated in this article. Since the mismatched parameters of individual systems, a kind of leader-following quasisynchronization issues is analyzed via impulsive control. To acquire appropriate im...

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Bibliographic Details
Main Authors: Ding, D. (Author), Ji, Z. (Author), Park, J.H (Author), Tang, Z. (Author), Wang, Y. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02910nam a2200529Ia 4500
001 10.1109-TCYB.2022.3168854
008 220630s2022 CNT 000 0 und d
020 |a 21682267 (ISSN) 
245 1 0 |a Dynamic Self-Triggered Impulsive Synchronization of Complex Networks With Mismatched Parameters and Distributed Delay 
260 0 |b Institute of Electrical and Electronics Engineers Inc.  |c 2022 
520 3 |a Synchronization of complex networks with nonlinear couplings and distributed time-varying delays is investigated in this article. Since the mismatched parameters of individual systems, a kind of leader-following quasisynchronization issues is analyzed via impulsive control. To acquire appropriate impulsive intervals, the dynamic self-triggered impulsive controller is devoted to predicting the available instants of impulsive inputs. The proposed controller ensures the control effects while reducing the control costs. In addition, the updating laws of the dynamic parameter is settled in consideration of error bounds to adapt to the quasisynchronization. With the utilization of the Lyapunov stability theorem, comparison method, and the definition of average impulsive interval, sufficient conditions for realizing the synchronization within a specific bound are derived. Moreover, with the definition of average impulsive gain, the parameter variation scheme is extended from the fixed impulsive effects case to the time-varying impulsive effects case. Finally, three numerical examples are given to show the effectiveness and the superiority of proposed mathematical deduction. Author 
650 0 4 |a Complex networks 
650 0 4 |a Complex networks 
650 0 4 |a Controllers 
650 0 4 |a Couplings 
650 0 4 |a Couplings 
650 0 4 |a Delay 
650 0 4 |a Delays 
650 0 4 |a Distributed delays 
650 0 4 |a distributed time-varying delay 
650 0 4 |a Distributed time-varying delay 
650 0 4 |a Dynamic self-triggered mechanism 
650 0 4 |a Dynamic self-triggered mechanism 
650 0 4 |a Error analysis 
650 0 4 |a extended parameter variation scheme 
650 0 4 |a Extended parameter variation scheme 
650 0 4 |a Impulsive effects 
650 0 4 |a Impulsive intervals 
650 0 4 |a Impulsive synchronization 
650 0 4 |a Mathematical models 
650 0 4 |a Monitoring 
650 0 4 |a Parameters variations 
650 0 4 |a Protocols 
650 0 4 |a Quasi synchronization 
650 0 4 |a quasisynchronization 
650 0 4 |a Synchronization 
650 0 4 |a Synchronization 
650 0 4 |a Time delay 
650 0 4 |a Time varying control systems 
650 0 4 |a Time varying networks 
700 1 0 |a Ding, D.  |e author 
700 1 0 |a Ji, Z.  |e author 
700 1 0 |a Park, J.H.  |e author 
700 1 0 |a Tang, Z.  |e author 
700 1 0 |a Wang, Y.  |e author 
773 |t IEEE Transactions on Cybernetics 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1109/TCYB.2022.3168854