Data-based composite control design with critic intelligence for a wastewater treatment platform

In this paper, by integrating neural network approximators, a data-based composite control technique is developed with critic learning implementation and wastewater treatment verification. The iterative adaptive critic framework is established involving dual heuristic dynamic programming (DHP), so a...

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Published inThe Artificial intelligence review Vol. 53; no. 5; pp. 3773 - 3785
Main Authors Wang, Ding, Ha, Mingming, Qiao, Junfei, Yan, Jun, Xie, Yingbo
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.06.2020
Springer
Springer Nature B.V
Subjects
Artificial Intelligence
Computer Science
Controllers
Dynamic programming
Iterative methods
Neural networks
Purification
Sewage
Wastewater treatment
Water treatment
Adaptive critic
Optimal feedback
Data-based composite control
Intelligent systems
Wastewater treatment
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Summary:In this paper, by integrating neural network approximators, a data-based composite control technique is developed with critic learning implementation and wastewater treatment verification. The iterative adaptive critic framework is established involving dual heuristic dynamic programming (DHP), so as to obtain an intelligent optimal controller. Besides, a steady control input is computed with the help of the neural identifier. Then, by combining the DHP controller and the steady control input, an effective composite control strategy is derived and applied to the proposed wastewater treatment platform. Through conducting experiments, it is observed that the dissolved oxygen concentration and the nitrate level can be maintained at setting points successfully, which results in an intelligent wastewater treatment system.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-019-09778-5