Compensation Control of Dissolved Oxygen in an Activated Sludge System via Hybrid Neuro Fuzzy Technique

Effective treatment of wastewater relies on a dissolved oxygen (DO) concentration level. Insufficient supply of the DO worsen the quality of the effluent (treated water) whereas too much high dissolved oxygen level maximizes energy consumption and cost. Therefore, DO control is highly crucial for economic, performance improvement as well as safety reasons. However, nonlinearities, influent fluctuations together with the time varying parameters of the system make DO control very difficult using classical control techniques. This paper presents compensation control of dissolved oxygen in the system based on hybrid neuro fuzzy technique. The performance of the proposed control algorithm is demonstrated by set-point tracking. For comparison a PID controller tuned using Zeigler-Nicholas method was used. The simulation results indicate that the proposed strategy is quite effective by tracking well the DO set-point trajectories. This kind of control strategy can be applied to real wastewater treatment system.