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Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach

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  • Xin, Li-Ping
  • Yu, Bo
  • Zhao, Lin
  • Yu, Jinpeng

Abstract

This work demonstrates an adaptive fuzzy backstepping control for a two cascaded continuous stirred tank reactors (CSTRs) system based on the dynamic surface control (DSC). The proposed controller is able to ensure the internal stabilization of the closed-loop system and render outputs track their reference signals asymptotically, although the CSTRs system is highly nonlinear and strong coupling. The effective and robust performance of the proposed controller in this research is certificated by the simulation analysis. Compared with previous researches, the on-line computation of controller is effectively reduced, which means that the proposed controller is easy to implement in engineering. The adaptive fuzzy dynamic surface control appears the potential for CSTRs process in mill operation.

Suggested Citation

  • Xin, Li-Ping & Yu, Bo & Zhao, Lin & Yu, Jinpeng, 2020. "Adaptive fuzzy backstepping control for a two continuous stirred tank reactors process based on dynamic surface control approach," Applied Mathematics and Computation, Elsevier, vol. 377(C).
    • Handle: RePEc:eee:apmaco:v:377:y:2020:i:c:s0096300320301077
    DOI: 10.1016/j.amc.2020.125138
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    References listed on IDEAS

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    Cited by:

    1. Li, Jiahao & Liu, Yu & Yu, Jinyong, 2022. "A new result on semi-synchronous event-triggered backstepping robust control for a class of non-Lipschitzian networked systems," Applied Mathematics and Computation, Elsevier, vol. 424(C).
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    3. Zhang, Yanqi & Wang, Zhenlei & Wang, Xin, 2023. "Adaptive modified prescribed performance constraint control for uncertain nonlinear discrete-time systems," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    4. Yoo, Sung Jin, 2021. "Decentralized event-triggered adaptive control of a class of uncertain interconnected nonlinear systems using local state feedback corrupted by unknown injection data," Applied Mathematics and Computation, Elsevier, vol. 399(C).

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