Advances in Generalized and Constrained Generalized Predictive Control withApplication to a Dynamometer Model

摘要

The Stable Generalized Predictive Control (SGPC) and Constrained StableGeneralized Predictive Control (CSGPC) algorithms are described. The advantages of these algorithms over existing ones are presented. The efficacy of CSGPC was illustrated by means of a design study on a model of a dynamometer feedback control system. The simulation results show that an approach to constraints could be disastrously wrong and that constraint inequality during the optimization stage must be taken into account. CSGPC does that and produces stable and optimal results, and overcomes problems of short term infeasibility.