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An improved robust finite-time dissipative control for uncertain fuzzy descriptor systems with disturbance

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  • Zhan Su
  • Jun Ai
  • Qingling Zhang
  • Naixue Xiong

Abstract

In this paper, finite-time robust control problems are investigated for Takagi– Sugeno fuzzy descriptor systems. We provide a novel sufficient condition for robust finite-time admissibility of Takagi– Sugeno fuzzy descriptor systems, involving a group of coupled linear matrix inequalities (LMIs), which guarantee dissipative performance, reduce conservativeness and improve LMIs forms. Second, corresponding controllers are developed based on both parallel distributed compensation and non-parallel distributed compensation. Simulations demonstrate the effectiveness of the proposed control approach.

Suggested Citation

  • Zhan Su & Jun Ai & Qingling Zhang & Naixue Xiong, 2017. "An improved robust finite-time dissipative control for uncertain fuzzy descriptor systems with disturbance," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(8), pages 1581-1596, June.
    • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:8:p:1581-1596
    DOI: 10.1080/00207721.2016.1277405
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    References listed on IDEAS

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    1. Zhan Su & Qingling Zhang & Jun Ai, 2013. "Practical and finite-time fuzzy adaptive control for nonlinear descriptor systems with uncertainties of unknown bound," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(12), pages 2223-2233.
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    Cited by:

    1. Obaid Alshammari & Mourad Kchaou & Houssem Jerbi & Sondess Ben Aoun & Víctor Leiva, 2022. "A Fuzzy Design for a Sliding Mode Observer-Based Control Scheme of Takagi-Sugeno Markov Jump Systems under Imperfect Premise Matching with Bio-Economic and Industrial Applications," Mathematics, MDPI, vol. 10(18), pages 1-28, September.
    2. Mu, Yunfei & Zhang, Huaguang & Su, Hanguang & Wang, Yingchun, 2021. "Robust normalization and H∞ stabilization for uncertain Takagi-Sugeno fuzzy singular systems with time-delays," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    3. Ai, Jun & Cai, Yifang & Su, Zhan & Zhang, Kuan & Peng, Dunlu & Chen, Qingkui, 2022. "Predicting user-item links in recommender systems based on similarity-network resource allocation," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).

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