Abstract

In this research, hierarchical control strategies are developed for biological wastewater treatment plants (WWTPs) to reduce the operational expenses. The benchmark simulation model no. 1 (BSM1) is used as the working platform which is developed based on activated sludge model no. 1 (ASM1) to control dissolved oxygen in aerobic reactors and nitrate levels in anoxic reactors. Fractional PI (FPI) controllers are designed at the lower level and model predictive control (MPC) and a fuzzy controller are designed at higher level in order to achieve enhanced set-point tracking. Initially, linear state space model is developed around the operating point using prediction-error method for lower level. For identification of the higher level model, the lower level control loop is closed in a feedback sense with the designed controller. Based on the identified model in the higher level, the controllers are designed. This paper presents two combinations of hierarchical control strategies: FPI-Fuzzy and FPI-MPC. It is observed that FPI controller at the lower level and MPC controller at the higher level results in better plant performance with better set-point tracking with reduced operational costs. It is observed that FPI-Fuzzy control strategy results in better EQI of 7041.7 for storm weather condition which also resulted in 48% reduction in total nitrogen violations and FPI-MPC results in better OCI of 17119.6 and this strategy resulted in nearly 38% reduction in total nitrogen violations. A significant improvement in the plant performance is observed for dry and rain weather conditions as well.

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