Adaptive critic design with weight allocation for intelligent learning control of wastewater treatment plants - Details

Author：

Wang, D. (Wang, D..) | Ma, H. (Ma, H..) | Ren, J. (Ren, J..) | Gao, N. (Gao, N..) | Qiao, J. (Qiao, J..)

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Abstract：

With　the　deepening　of　modernization　and　industrialization,　the　issues　of　water　pollution　and　scarcity　have　become　more　pressing.　To　address　these　issues,　many　wastewater　treatment　factories　have　been　built　to　improve　the　reuse　of　water　resources.　However,　the　control　of　the　wastewater　treatment　process　(WWTP)　is　a　complex　task　due　to　the　highly　nonlinear　and　strongly　coupled　nature.　It　is　challenging　to　develop　the　accurate　mechanism　models　of　the　wastewater　treatment　system.　The　improvement　of　the　efficiency　for　the　WWTP　is　crucial　to　safeguard　the　urban　ecological　environment.　In　this　paper,　adaptive　critic　with　weight　allocation　(ACWA)　is　developed　to　address　the　optimal　control　problem　in　the　WWTP.　Different　from　the　previous　methods　of　the　WWTP,　system　modeling　is　not　adopted　in　this　paper,　which　meets　the　actual　physical　background　of　the　wastewater　treatment　system　to　a　great　extent.　In　addition,　the　actor-critic　algorithm　in　reinforcement　learning　is　used　as　the　basic　structure　in　the　ACWA.　It　is　worth　noting　that　a　novel　weighted　action-value　function　and　the　advantage　function　are　introduced　in　the　weight　updating　process　of　the　action　network　and　the　critic　network.　The　experimental　results　show　that　the　control　accuracy　of　the　ACWA　is　greatly　improved　compared　with　the　previous　control　methods.　©　2024　Elsevier　Ltd

Keyword：

Reinforcement learning Neural networks Actor-critic Adaptive critic design Wastewater treatment processes

Author Community：

[ 1 ] [Wang D.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Wang D.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Wang D.]Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Wang D.]Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China
[ 5 ] [Ma H.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 6 ] [Ma H.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 7 ] [Ma H.]Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China
[ 8 ] [Ma H.]Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China
[ 9 ] [Ren J.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 10 ] [Ren J.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 11 ] [Ren J.]Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China
[ 12 ] [Ren J.]Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China
[ 13 ] [Gao N.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 14 ] [Gao N.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 15 ] [Gao N.]Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China
[ 16 ] [Gao N.]Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China
[ 17 ] [Qiao J.]Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 18 ] [Qiao J.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China
[ 19 ] [Qiao J.]Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China
[ 20 ] [Qiao J.]Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China

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Source ：

Engineering Applications of Artificial Intelligence

ISSN： 0952-1976

Year： 2024

Volume： 133

8 . 0 0 0

JCR@2022

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count： 8

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 16

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