Multi-objective optimization based controller design for improved wastewater treatment plant operation

Wastewater treatment plants (WWTPs) are highly complex and nonlinear processes. The challenge lies in the design of a control strategy to lower the operational costs and to enhance the effluent quality simultaneously. In this research, PI controllers are designed for control of biological WWTPs and Benchmark Simulation Model No. 1 (BSM1) is used as a working platform. Genetic Algorithms which are a subclass of evolutionary search algorithms are used to determine optimal PI controller parameters to achieve improved effluent quality with minimum operational expenses. Different objective functions such as Indices for Effluent Quality and Operational Cost, and Integral Square Error (ISE) for the design of controllers are considered. A Pareto optimal curve is plotted for different conditions and the best combination is evaluated. The results indicated that the controllers designed using this approach provided improved WWTP operation. (C) 2021 Elsevier B.V. All rights reserved.