Multiple-model off-line predictive control for fast time-varying systems

To track the wide range of operating points of fast time-varying processes, a novel multiple model off-line predictive control algorithm is presented. The proposed method is a combination of multiple model strategy and predictive control. Firstly, we locally describe the original nonlinear system around an operating point employing linear time varying (LTV) model. Then the offline model predictive control (OMPC) algorithm is adopted to design local controller for LTV model, whose low computation burden makes it be able to control the fast time-varying process. To track the wide range of operating point, the multiple-model strategy is exploited. By estimating the stable region of local OMPC and selecting appropriate middle operating points, the stable switch between controllers can be guaranteed. Finally, a numerical simulation is given to illustrate the implementation and effectiveness of the proposed method.