The study of multiple model predictive control in wastewater treatment processes

A multiple model predictive control strategy dealing with nonlinear model-based predictive control (NMPC) is proposed in this paper. It is used to deal with control problem of strong nonlinear systems-wastewater treatment processes. Firstly a multi-model modeling method based on local model is given. The modeling idea is to rind sonic data matching with the current working point from vast historical system input-output datasets, then to develop a local model using local polynomial fitting (LPF) algorithm. With the change of working points, multiple local models are built. Combining the obtained multiple models with predictive control, a multiple model predictive control strategy is developed, thus solves the control problem of a sort of unknown-structure nonlinear system based on vast history data only. The effectiveness of the proposed method is demonstrated by simulation results.