A MIXED LOGIC ENHANCED MULTI-MODEL SWITCHING PREDICTIVE CONTROLLER FOR NONLINEAR DYNAMIC PROCESS

T. Zou, X. Wang, S.Y. Li, and Q.M. Zhu

Keywords

Nonlinear model predictive control, multiple model switching predictive control, mixed logic, mixed integer quadratic programming

Abstract

In this study a procedure to design multiple model switching predictive controllers (MMSPC) is proposed for the nonlinear dynamic processes with large operation regions. To facilitate the MMSPC design, a general mixed logic dynamic system (MLDS) model is proposed for approximating the nonlinear processes. A major contribution of this study is to integrate a number of techniques to form a novel procedure, and therefore to make multistep state and output predictions effectively realizable within the frame of multiple model switching control. A case for support is presented to demonstrate the efficiency of the design procedure.

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