期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 29, 期 12, 页码 5812-5822出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2018.2812098
关键词
Complex dynamical network (CDNs); event-triggering; pinning control; stochastic stability; synchronization control
类别
资金
- National Natural Science Foundation of China [11501065, 61525305, 61773004, 61773209]
- Research Fund for the Taishan Scholar Project of Shandong Province of China
- Program of Chongqing Innovation Team Project in University [CXTDX201601022]
- Basic and Frontier Research Projects of Chongqing [cstc2015jcyjA00033, cstc2017jcyjA1353]
- Natural Science Foundation of Chongqing Education Committee [KJ1600504]
- Alexander von Humboldt Foundation of Germany
This paper is concerned with the synchronization analysis and control problems for a class of nonlinear discrete-time stochastic complex dynamical networks (CDNs) consisting of identical nodes. The discrete-time stochastic dynamical networks under consideration are quite general that account for asymmetric coupling configuration, nonlinear inner coupling structures as well as nonidentical exogenous disturbances. By resorting to both the error bound and the synchronization probability, a notion of quasi-synchronization in probability is first introduced to assess the synchronization performance of the addressed CDNs. An event-triggered pinning feedback control strategy is adopted to control a small fraction of the network nodes with hope to reduce the frequency of updating and communication in the control process while preserving the desired dynamical behaviors of the controlled networks. By using the Lyapunov function method and the stochastic analysis techniques, a general framework is established within which the problems of dynamics analysis and controller synthesis are solved for the closed-loop stochastic dynamical networks. Two numerical examples and their simulations are presented to illustrate the effectiveness and the usefulness of our theoretical results.
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