Research on optimization control model and algorithm for sewage treatment process

The present research addresses the challenge of optimizing control in the wastewater treatment process, presenting a refined control model rooted in the particle swarm optimization (PSO) algorithm. Through a comprehensive examination of the nonlinear and interdependent multivariable dynamics inherent in wastewater treatment systems, a tailored control model suitable for real-world operational conditions is developed. In the algorithm design phase, the PSO algorithm is employed to fine-tune control parameters, enhancing both the system's stability and overall treatment performance. The creation of the simulation framework integrates several crucial elements of the wastewater treatment process, thereby ensuring the model's robustness and practical applicability in diverse operational scenarios. The results from the simulation highlight that the proposed optimization control model offers considerable benefits in minimizing energy usage while boosting treatment effectiveness, demonstrating strong adaptability and global convergence characteristics. Subsequent data analysis corroborates the model's precision and practicality, delivering valuable technical insights for the intelligent optimization of wastewater treatment processes.