Intellectual optimized controller for wastewater treatment plant model

This research proposes an Intellectually Optimized PID (OPID) controller to enhance biological Wastewater Treatment Plant (WWTP) performance by targeting key effluent parameters, Biochemical Oxygen Demand (BOD₅) and Chemical Oxygen Demand (COD). Traditional PID controllers, though simple and cost-effective, are limited in handling the nonlinear dynamics of WWTPs. To overcome this, an auto-tuning technique based on a genetic algorithm (GA) is introduced, which efficiently optimizes PID parameters through reproduction, crossover, and mutation, ensuring global optimality. Using Benchmark Simulation Model No. 1 (BSM1), the OPID controller demonstrates improved effluent quality and reduced operational costs compared to conventional tuning methods. The approach offers a robust, efficient solution for nonlinear system control, with potential applications in various industrial domains.