Multiplexed model predictive control weighting selection using Genetic Algorithm

Abstract

This paper presents the application of Genetic Algorithm (GA) to find the optimal weighting of multiplexed model predictive control (MMPC). Using GA, the selection procedure can be done to ensure the best possible combination of the weighting parameters of MMPC. A bake plate system model controlled using MMPC is used to demonstrate the effect of the selected parameters using GA.