Noise-to-state exponentially stabilizing (state, input)-disturbed CSTRs with non-vanishing noise

Yafei Lu;Chuanhou Gao;Denis Dochain
(2022) Automatica (Online) — (2022)

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Authors
  • Yafei LuZheijang University
    Author
  • Chuanhou GaoZheijang University
    Author
  • Denis DochainUCLouvain
    Author
Abstract
In this paper, we have proposed a (state, input)-disturbed CSTR (sidCSTR) model that considers unknown but bounded fluctuations in kinetics, flow rates, and heat exchange. A feedback control law is developed that stabilizes the sidCSTR system to reach noise-to-state exponential stability (NSES). The lower bound of the distribution for the state of the NSES sidCSTR system is analyzed both from the probability domain and the time domain. The performance and the validity of the proposed method are demonstrated using a case study dealing with a second-order reversible reaction.
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Yafei Lu, Chuanhou Gao, & Denis Dochain. (2022). Noise-to-state exponentially stabilizing (state, input)-disturbed CSTRs with non-vanishing noise. Automatica (Online). Accepted/in-press. https://hdl.handle.net/2078.5/107896 (Original work published 2022)