Stochastic optimisation algorithm for optimisation of controller parameters for control of dissolved oxygen in wastewater treatment plant

Abstract

Wastewater treatment plants (WWTPs) are very important facilities for mankind. They enable the removal and neutralisation of man-made pollutants. Therefore, it is important for wastewater treatment plants to operate as efficiently as possible so that the level of pollutants in the treated wastewater meets specific requirements. This paper concerns the design of a hierarchical nonlinear adaptive control system for dissolved oxygen (DO) concentration in wastewater for a biological Sequential Batch Reactor (SBR). The parameters of the control system used are optimised to ensure the best possible control quality and low energy consumption at the same time. Based on data collected from a case study WWTP, an Activated Sludge Model 2d (ASM2d) of the biological processes and a model of the aeration system are applied. The Coyote Optimization Algorithm (COA) is used to optimize the adaptive controller parameters. A Proportional-Integral-Derivative (PID) control system is also developed to compare the control results. The results obtained from simulation studies for both control systems are presented. As a result of optimised parameters, higher wastewater treatment efficiency and reduced electricity consumption are achieved.