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L2−L∞ synchronization for singularly perturbed complex networks with semi-Markov jump topology

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Listed:
  • Liang, Kun
  • Dai, Mingcheng
  • Shen, Hao
  • Wang, Jing
  • Wang, Zhen
  • Chen, Bo

Abstract

This paper is concerned with the problem of L2--L∞ synchronization for singularly perturbed complex networks (SPCNs) with semi-Markov jump topology, in which the phenomenon of the singular perturbation is fully taken into consideration. The topology of complex dynamical network is time-varying switching regulated by the semi-Markov jump mechanism. The priority of this work is to obtain some conditions which ensure the underlying complex dynamical network (CDN) is stochastically synchronized with a stated L2--L∞ performance level. Based on Lyapunov method and convex optimization technique, the synchronization conditions can be obtained via solving convex optimization problems. Finally, the correctness and validity of our proposed synchronization method are well demonstrated by a simulation example.

Suggested Citation

  • Liang, Kun & Dai, Mingcheng & Shen, Hao & Wang, Jing & Wang, Zhen & Chen, Bo, 2018. "L2−L∞ synchronization for singularly perturbed complex networks with semi-Markov jump topology," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 450-462.
    • Handle: RePEc:eee:apmaco:v:321:y:2018:i:c:p:450-462
    DOI: 10.1016/j.amc.2017.10.039
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    8. Wang, Yao & Guo, Jun & Liu, Guobao & Lu, Junwei & Li, Fangyuan, 2021. "Finite-time sampled-data synchronization for uncertain neutral-type semi-Markovian jump neural networks with mixed time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 403(C).
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    13. Fan, Gaofeng & Ma, Yuechao, 2023. "Fault-tolerant fixed/preassigned-time synchronization control of uncertain singularly perturbed complex networks with time-varying delay and stochastic disturbances," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
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    15. Tai, Weipeng & Teng, Qingyong & Zhou, Youmei & Zhou, Jianping & Wang, Zhen, 2019. "Chaos synchronization of stochastic reaction-diffusion time-delay neural networks via non-fragile output-feedback control," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 115-127.
    16. Wang, Jing & Liang, Kun & Huang, Xia & Wang, Zhen & Shen, Hao, 2018. "Dissipative fault-tolerant control for nonlinear singular perturbed systems with Markov jumping parameters based on slow state feedback," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 247-262.
    17. Yangjie Chen & Fan Zhang & Jianning Li, 2022. "Anti-Disturbance Fault-Tolerant Constrained Consensus for Time-Delay Faulty Multi-Agent Systems with Semi-Markov Switching Topology," Mathematics, MDPI, vol. 10(23), pages 1-17, December.
    18. Huang, Xin & Liu, Yamin & Wang, Yang & Zhou, Jianping & Fang, Muyun & Wang, Zhen, 2020. "L2−L∞ consensus of stochastic delayed multi-agent systems with ADT switching interaction topologies," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    19. Jiao, Ticao & Park, Ju H. & Zong, Guangdeng & Liu, Jian & Chen, Yu, 2019. "Stochastic stability analysis of switched genetic regulatory networks without stable subsystems," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 261-277.
    20. Yang, Te & Chen, Guoliang & Xia, Jianwei & Wang, Zhen & Sun, Qun, 2019. "Robust H∞ filtering for polytopic uncertain stochastic systems under quantized sampled outputs," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 688-701.

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