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New insights on stability of sampled-data systems with time-delay

Author

Listed:
  • Zeng, Hong-Bing
  • Zhai, Zheng-Liang
  • He, Yong
  • Teo, Kok-Lay
  • Wang, Wei

Abstract

This paper analyses the stability of sampled-data systems with time-delay. By employing a two-sided looped-functional approach, some improved conditions are derived to guarantee the stability of the system under consideration. Then, based the conditions, some intrinsic relationships between sampled-data period and time delay are obtained. From the illustrative example being solved by the proposed approach, it is observed that the results obtained are significantly better than those obtained by existing methods. More importantly, from the simulation being carried out, it is discovered that, contrary to the findings in previous studies, time-delays in a system may enlarge the interval of sampled-data periods and accelerate the rate of convergence of the system states, rather than deteriorate the system performance.

Suggested Citation

  • Zeng, Hong-Bing & Zhai, Zheng-Liang & He, Yong & Teo, Kok-Lay & Wang, Wei, 2020. "New insights on stability of sampled-data systems with time-delay," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:apmaco:v:374:y:2020:i:c:s0096300320300102
    DOI: 10.1016/j.amc.2020.125041
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    References listed on IDEAS

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    1. Lee, Tae H. & Park, Ju H. & Jung, Hoyoul, 2018. "Network-based H∞ state estimation for neural networks using imperfect measurement," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 205-214.
    2. Zeng, Hong-Bing & Liu, Xiao-Gui & Wang, Wei, 2019. "A generalized free-matrix-based integral inequality for stability analysis of time-varying delay systems," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 1-8.
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    Cited by:

    1. Huan, Mingchen & Li, Chuandong, 2023. "Synchronization of reaction–diffusion neural networks with sampled-data control via a new two-sided looped-functional," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Vadivel, R. & Hammachukiattikul, P. & Gunasekaran, Nallappan & Saravanakumar, R. & Dutta, Hemen, 2021. "Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Zhang, He & Xu, Shengyuan & Zhang, Zhengqiang & Chu, Yuming, 2022. "Practical stability of a nonlinear system with delayed control input," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    4. Chen, Wu-Hua & Sun, Hao & Lu, Xiaomei, 2024. "A variable gain impulsive observer for perturbed Lipschitz nonlinear systems with delayed discrete measurements," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    5. Zhong, Qishui & Han, Sheng & Shi, Kaibo & Zhong, Shouming & Cai, Xiao & Kwon, Oh-Min, 2022. "Distributed secure sampled-data control for distributed generators and energy storage systems in microgrids under abnormal deception attacks," Applied Energy, Elsevier, vol. 326(C).
    6. Huang, Yi-Bo & He, Yong, 2022. "Bessel-type inequality in semi-inner-product spaces and its application to stability analysis of discrete-time systems with distributed delays," Applied Mathematics and Computation, Elsevier, vol. 427(C).

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