Eigenvector Based Multiobjective Model Predictive Control for Wastewater Treatment Process

Model predictive control is an effective way to achieve the control of wastewater treatment process (WWTP). However, it is a challenge to control multiple objectives due to the complexity of WWTP. To solve this problem, an eigenvector based multiobjective model predictive control (EMMPC) strategy is developed for WWTP to handle the conflicting objectives. First, a multiobjective control scheme is designed with adaptive fuzzy neural network prediction (AFNNP) model and gradient eigenvector optimization (GEO) algorithm. Then, AFNNP can be used to describe the nonlinear of WWTP to predict the controlled variables. Second, GEO is presented to obtain the control laws of the multiple control objectives. Specifically, GEO can reduce the computational burden by avoiding the determination of the control objective weights. Third, the stability of EMMPC is provided in theory. Finally, EMMPC is implemented on the benchmark simulation platform to demonstrate the effectiveness of the presented multiobjective control method.