A mixed logic enhanced multi-model switching predictive controller for nonlinear dynamic process

Authors:
T. Zou;X. Wang;S. Y. Li;Q. M. Zhu
Affiliations:
Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China;University of the West of England, Bristol, UK
Venue:
Control and Intelligent Systems
Year:
2007

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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.