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Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system

Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system The wastewater treatment is an effective method for alleviating the shortage of water resources. In this article, a data‐driven iterative adaptive tracking control approach is developed to improve the control performance of the dissolved oxygen concentration and the nitrate nitrogen concentration in the nonlinear wastewater treatment plant. First, the model network is established to obtain the steady control and evaluate the new system state. Then, a nonquadratic performance functional is provided to handle asymmetric control constraints. Moreover, the new costate function and the tracking control policy are derived by using the dual heuristic dynamic programming algorithm. In the present control scheme, two neural networks are constructed to approximate the costate function and the tracking control law. Finally, the feasibility of the proposed algorithm is confirmed by applying the designed strategy to the wastewater treatment plant. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Robust and Nonlinear Control Wiley

Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system

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References (38)

Publisher
Wiley
Copyright
© 2021 John Wiley & Sons, Ltd.
ISSN
1049-8923
eISSN
1099-1239
DOI
10.1002/rnc.5639
Publisher site
See Article on Publisher Site

Abstract

The wastewater treatment is an effective method for alleviating the shortage of water resources. In this article, a data‐driven iterative adaptive tracking control approach is developed to improve the control performance of the dissolved oxygen concentration and the nitrate nitrogen concentration in the nonlinear wastewater treatment plant. First, the model network is established to obtain the steady control and evaluate the new system state. Then, a nonquadratic performance functional is provided to handle asymmetric control constraints. Moreover, the new costate function and the tracking control policy are derived by using the dual heuristic dynamic programming algorithm. In the present control scheme, two neural networks are constructed to approximate the costate function and the tracking control law. Finally, the feasibility of the proposed algorithm is confirmed by applying the designed strategy to the wastewater treatment plant.

Journal

International Journal of Robust and Nonlinear ControlWiley

Published: Sep 25, 2021

Keywords: ; ; ; ;

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