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Author:

Han, H. (Han, H..) | Tang, Z. (Tang, Z..) | Li, H. (Li, H..) | Yang, H. (Yang, H..) | Wu, X. (Wu, X..)

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Scopus SCIE

Abstract:

Wastewater treatment processes (WWTPs) possess the characteristics of multiple disturbances, which make it difficult to achieve the accurate control of desired dissolved oxygen (DO) concentration. To address this issue, this paper proposes a robust inverse control strategy based on disturbance boundary estimation (DBE-RIC). First, a nonlinear disturbance observer based on disturbance boundary estimation is introduced to reconstruct the disturbances, which enables DBE-RIC to deal with internal and external disturbances simultaneously. Second, an inverse controller based on inverse transformation and the reconstructed disturbance signals is designed to obtain the control law under unknown dynamics of WWTPs. Third, a projection operator is presented to adjust the controller parameters online. Then, the RIC controller can accomplish the accurate tracking control of DO concentration. Furthermore, the stability of the proposed strategy in the sense of Lyapunov and the guidelines associated with the control parameters are given. Lastly, the experimental results on the benchmark simulation platform BSM1 demonstrate the feasibility and superiority of DBE-RIC compared to other methods. © 2024 John Wiley & Sons Ltd.

Keyword:

wastewater treatment process dissolved oxygen disturbance boundary estimation robust inverse control

Author Community:

  • [ 1 ] [Han H.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 2 ] [Han H.]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, China
  • [ 3 ] [Tang Z.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 4 ] [Tang Z.]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, China
  • [ 5 ] [Li H.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 6 ] [Li H.]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, China
  • [ 7 ] [Yang H.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 8 ] [Yang H.]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, China
  • [ 9 ] [Wu X.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 10 ] [Wu X.]Engineering Research Center of Digital Community Ministry of Education, Beijing University of Technology, Beijing, China

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Source :

International Journal of Robust and Nonlinear Control

ISSN: 1049-8923

Year: 2024

3 . 9 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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