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Event-Triggered State Estimation for Uncertain Systems with Binary Encoding Transmission Scheme

Author

Listed:
  • Zun Li

    (School of Automation, Qingdao University, Qingdao 266071, China)

  • Binqiang Xue

    (School of Automation, Qingdao University, Qingdao 266071, China)

  • Youyuan Chen

    (School of Automation, Qingdao University, Qingdao 266071, China)

Abstract

This paper proposes an event-triggered state estimation method for parameter-uncertain systems with a binary encoding transmission scheme. Firstly, a binary encoding transmission scheme is introduced between the state estimator and the system to improve the efficiency of network communication. Secondly, an event-triggering mechanism (ETM) is designed to ensure the accuracy of state estimation and reduce the computational burden of the state estimator. At the event-triggered moments, considering the uncertainty of the system, the binary encoding transmission scheme, and the ETM, a moving horizon estimator (MHER) is designed using the robust least squares optimization method to obtain optimal state estimation. At the no-event-triggered moments, the state estimation of the system is computed based on an open-loop state estimator (OLER). Furthermore, stability analysis showed that the state estimation error of the proposed method is bounded. Finally, the practical value of the proposed in this paper is confirmed through numerical simulation.

Suggested Citation

  • Zun Li & Binqiang Xue & Youyuan Chen, 2023. "Event-Triggered State Estimation for Uncertain Systems with Binary Encoding Transmission Scheme," Mathematics, MDPI, vol. 11(17), pages 1-16, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3679-:d:1225727
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    References listed on IDEAS

    as
    1. Shoudong Wang & Binqiang Xue, 2023. "Distributed Moving Horizon Fusion Estimation for Nonlinear Constrained Uncertain Systems," Mathematics, MDPI, vol. 11(6), pages 1-22, March.
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