Multi-objective Optimal Control of Wastewater Treatment Based on IMOPSO Algorithm

In order to achieve the goal of quality assurance and consumption reduction in wastewater treatment, an intelligent optimization control strategy for wastewater treatment based on improved multi-objective particle swarm optimization algorithm (IMOPSO) is proposed. Firstly, by analyzing the dynamic characteristics of the wastewater treatment process, a soft measurement model of energy consumption and water quality is established. Then, the improved multi-objective particle swarm algorithm (IMOPSO) is used to optimize and calculate the model, and in IMOPSO, the adaptive grid and congestion distance are used to optimize and improve the selection method of the global leader and the external archive size control strategy, and the fine-tuning parameters and cosine factor are introduced to dynamically adjust the flight of particles in the population to improve the convergence and diversity of the algorithm. Finally, the PID controller is selected to realize the tracking control of the optimized setpoint. Simulation results show that this strategy can effectively reduce energy consumption and maintain good water quality.