Optimized fuzzy sliding mode control for energy-efficient wastewater treatment

Wastewater treatment is essential for environmental sustainability and public health. However, existing control strategies struggle with system nonlinearity, disturbances, and high energy consumption (EC). This study proposes a robust self-organizing fuzzy sliding mode controller (SOFSMC) to enhance effluent quality, energy efficiency, and system adaptability in wastewater treatment plants (WWTPs). By integrating sliding mode control (SMC) with a self-organizing fuzzy logic system (SOFLS), the controller improves adaptability and reduces the chattering effect. The newly developed JAYA optimization algorithm is used to fine-tune control parameters, optimizing both energy use and pollutant removal. Simulation results show SOFSMC outperforms proportional integral derivative (PID), standard SMC, and fuzzy logic controllers (FLCs). EQI is reduced by 48.3% and 28.4% compared to PID and FLC, respectively. EC is significantly optimized, and settling time and chattering amplitude (CA) are reduced by 28% and 75%, respectively. SOFSMC offers a scalable, energy-efficient, and robust solution for advanced wastewater treatment.