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Adaptive Regulation for Hammerstein and Wiener Systems with Event-Triggered Observations

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Abstract

The paper considers the adaptive regulation for the Hammerstein and Wiener systems with event-triggered observations. The authors adopt a direct approach, i.e., without identifying the unknown parameters and functions within the systems, adaptive regulators are directly designed based on the event-triggered observations on the regulation errors. The adaptive regulators belong to the stochastic approximation algorithms and under moderate assumptions, the authors prove that the adaptive regulators are optimal for both the Hammerstein and Wiener systems in the sense that the squared regulation errors are asymptotically minimized. The authors also testify the theoretical results through simulation studies.

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Author information

Authors and Affiliations

  1. Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Xiaotao Ren & Wenxiao Zhao

  2. Department of Control Science and Engineering, Jilin University, Changchun, 130025, China

    Jinwu Gao

Authors
  1. Xiaotao Ren
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  2. Wenxiao Zhao
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  3. Jinwu Gao
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Corresponding author

Correspondence to Wenxiao Zhao.

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The authors declare no conflict of interest.

Additional information

This paper was supported by the National Key Research and Development Program of China under Grant No. 2018YFA0703800, the Chinese Academy of Sciences (CAS) Project for Young Scientists in Basic Research under Grant No. YSBR-008, and the Strategic Priority Research Program of CAS under Grant No. XDA27000000.

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Ren, X., Zhao, W. & Gao, J. Adaptive Regulation for Hammerstein and Wiener Systems with Event-Triggered Observations. J Syst Sci Complex 36, 1878–1904 (2023). https://doi.org/10.1007/s11424-023-2005-3

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  • DOI: https://doi.org/10.1007/s11424-023-2005-3

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