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Extended dissipative sliding mode control for nonlinear networked control systems via event-triggered mechanism with random uncertain measurement

Author

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  • Liu, Yu-An
  • Tang, Shengdao
  • Liu, Yufan
  • Kong, Qingkai
  • Wang, Jing

Abstract

This work concentrates on addressing the sliding mode control problem of continuous-time nonlinear networked control systems. Considering the state information may not be utterly available in practice, a state observer model is designed to estimate the state information. Meanwhile, a type of discrete-time event-triggered mechanism is utilized to filter the sampled signal for reducing the occupation of network bandwidths and the transmission rate of resources. In addition, a random variable obeying the Bernoulli distribution is adopted to describe the phenomenon of uncertainties randomly occurring in the measurement. With the aid of the Lyapunov stability and sliding mode control theory, some sufficient criteria are given to both guarantee the mean-square asymptotic stability of the overall closed-loop system with an extended dissipative performance, and the reachability of predefined sliding surface. Whereafter, the event-triggered weighting matrix, and gains of sliding mode controller and with observer are obtained by solving the matrix convex optimization problem. Finally, the feasibility of the presented scheme is demonstrated through two illustrative examples.

Suggested Citation

  • Liu, Yu-An & Tang, Shengdao & Liu, Yufan & Kong, Qingkai & Wang, Jing, 2021. "Extended dissipative sliding mode control for nonlinear networked control systems via event-triggered mechanism with random uncertain measurement," Applied Mathematics and Computation, Elsevier, vol. 396(C).
  • Handle: RePEc:eee:apmaco:v:396:y:2021:i:c:s0096300320308547
    DOI: 10.1016/j.amc.2020.125901
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    References listed on IDEAS

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    Cited by:

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    19. Jung, H.I. & Han, S.Y. & Singh, Satnesh & Lee, S.M., 2021. "Polynomially parameter dependent exponential stabilization of sampled-data LPV systems," Applied Mathematics and Computation, Elsevier, vol. 411(C).

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