Fault-tolerant synchronization control for complex dynamical networks with semi-Markov jump topology

2017 ◽  
Vol 312 ◽  
pp. 36-48 ◽  
Author(s):  
Dan Ye ◽  
Xiang Yang ◽  
Lei Su
Keyword(s):  
Fault Tolerant ◽  
Complex Dynamical Networks ◽  
Synchronization Control ◽  
Markov Jump ◽  
Dynamical Networks

scholarly journals Dissipativity-Based Synchronization of Mode-Dependent Complex Dynamical Networks with Semi-Markov Jump Topology

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Chao Ma ◽  
Wei Wu ◽  
Yidao Ji
Keyword(s):  
Markov Process ◽  
Complex Dynamical Networks ◽  
Matrix Transformation ◽  
Synchronization Control ◽  
Markov Jump ◽  
Dynamical Networks ◽  
Semi Markov Process ◽  
Network Topologies ◽  
Simulation Results

This paper considers the synchronization control for mode-dependent complex dynamical networks (CDNs) based on dissipativity theory. Particularly, the network topologies of the CDNs are governed by the semi-Markov process. By applying the Lyapunov-Krasovskii method, mode-dependent sufficient synchronization criteria are established while satisfying the desired dissipativity performance. On the basis of matrix transformation, the synchronization controllers are further designed. The effectiveness of our obtained results is illustrated with simulation results.

scholarly journals Neural network based asynchronous synchronization for fuzzy hidden Markov jump complex dynamical networks

2021 ◽  
Author(s):  
Chao Ma ◽  
Liziyi Hao ◽  
Hang Fu
Keyword(s):  
Neural Network ◽  
Hidden Markov ◽  
Sufficient Conditions ◽  
Complex Dynamical Networks ◽  
Linear Matrix ◽  
Markov Jump ◽  
Dynamical Networks ◽  
Synchronization Problem ◽  
The Neural Network ◽  
Takagi Sugeno

AbstractThis paper investigates the drive-response synchronization problem of Takagi–Sugeno fuzzy hidden Markov jump complex dynamical networks. More precisely, a novel asynchronous synchronization control strategy is developed for coping with mismatched hidden jumping modes. Furthermore, the neural network is adopted with online learning laws for unknown function approximation. By taking advantage of Lyapunov method, sufficient conditions are established to ensure mean-square synchronization performance with disturbances. Based on the synchronization criterion, asynchronous controller gains are designed in terms of linear matrix inequalities. An illustrative example is finally given to validate the effectiveness of the proposed synchronization techniques.

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