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Author:

Qiao, Junfei (Qiao, Junfei.) | Zhao, Mingming (Zhao, Mingming.) | Wang, Ding (Wang, Ding.) (Scholars:王鼎) | Li, Menghua (Li, Menghua.)

Indexed by:

EI Scopus SCIE

Abstract:

The wastewater treatment process (WWTP) is beneficial for maintaining sufficient water resources and recycling wastewater. A crucial link of WWTP is to ensure that the dissolved oxygen (DO) concentration is continuously maintained at the predetermined value, which can actually be considered as a tracking problem. In this article, an experience replay-based action-dependent heuristic dynamic programming (ER-ADHDP) method is developed to design the model-free tracking controller to accomplish the tracking goal of the DO concentration. First, the online ER-ADHDP controller is regarded as a supplementary controller to conduct the model-free tracking control alongside a stabilizing controller with a priori knowledge. The online ER-ADHDP method can adaptively adjust weight parameters of critic and action networks, thereby continuously ameliorating the tracking result over time. Second, the ER technique is integrated into the critic and action networks to promote the data utilization efficiency and accelerate the learning process. Third, a rational stability result is provided to theoretically ensure the usefulness of the ER-ADHDP tracking design. Finally, simulation experiments including different reference trajectories are conducted to show the superb tracking performance and excellent adaptability of the proposed ER-ADHDP method.

Keyword:

wastewater treatment applications tracking control Action-dependent heuristic dynamic programming (ADHDP) adaptive dynamic programming (ADP) adaptive critic control

Author Community:

  • [ 1 ] [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 2 ] [Zhao, Mingming]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 3 ] [Wang, Ding]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 4 ] [Li, Menghua]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China
  • [ 5 ] [Qiao, Junfei]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 6 ] [Zhao, Mingming]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 7 ] [Wang, Ding]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 8 ] [Li, Menghua]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 王鼎

    [Wang, Ding]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intelligen, Beijing 100124, Peoples R China

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Source :

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

ISSN: 1551-3203

Year: 2024

Issue: 4

Volume: 20

Page: 6257-6265

1 2 . 3 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 7

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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