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Stability analysis and robust controller design for systems with mixed time-delays and stochastic nonlinearity via cone complementarity linearization

Author

Listed:
  • Zheng, Wei
  • Zhang, Zhiming
  • Sun, Fuchun
  • Lam, Hak Keung
  • Wen, Shuhuan

Abstract

The stochastic Takagi-Sugeno (T-S) fuzzy discrete dynamic output feedback control is investigated for a class of stochastic T-S fuzzy discrete networked control systems. Firstly, the T-S fuzzy model and stochastic Bernoulli theory are employed to approximate the discrete system plant. Secondly, the T-S fuzzy model and stochastic Bernoulli theory are employed to design the stochastic T-S fuzzy discrete dynamic output feedback controller. Thirdly, the stochastic Bernoulli theory is employed to describe the characteristics of random occurrence for multipath packet dropouts. The delay-dependent discrete Lyapunov functional and Schur complement are employed, the closed-loop system is stochastically finite-time bounded stable subject to (c1,c2,ω¯,N,R). The Schur complement and congruence transformation matrix are introduced to determine controller gain matrices. The cone complementarity linearization is applied to convert controller design into nonlinear minimization constraints for solving the nonconvex problem caused by fuzzy-basis-dependent LMIs. Simulations are given to show the effectiveness of proposed methods.

Suggested Citation

  • Zheng, Wei & Zhang, Zhiming & Sun, Fuchun & Lam, Hak Keung & Wen, Shuhuan, 2022. "Stability analysis and robust controller design for systems with mixed time-delays and stochastic nonlinearity via cone complementarity linearization," Applied Mathematics and Computation, Elsevier, vol. 430(C).
  • Handle: RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003265
    DOI: 10.1016/j.amc.2022.127252
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    References listed on IDEAS

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    1. Zhang, Zhiming & Zheng, Wei & Lam, H.K. & Wen, Shuhuan & Sun, Fuchun & Xie, Ping, 2020. "Stability analysis and output feedback control for stochastic networked systems with multiple communication delays and nonlinearities using fuzzy control technique," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    2. 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.
    3. Chen, Zongjie & Zhang, Yigang & Kong, Qingkai & Fang, Ting & Wang, Jing, 2022. "Observer-based H∞ control for persistent dwell-time switched networked nonlinear systems under packet dropout," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    4. Xie, Jiaquan & Yao, Zhibin & Gui, Hailian & Zhao, Fuqiang & Li, Dongyang, 2018. "A two-dimensional Chebyshev wavelets approach for solving the Fokker-Planck equations of time and space fractional derivatives type with variable coefficients," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 197-208.
    5. Wang, Haitao & Chen, Xiangyong & Wang, Jing, 2022. "H∞ sliding mode control for PDT-switched nonlinear systems under the dynamic event-triggered mechanism," Applied Mathematics and Computation, Elsevier, vol. 412(C).
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