Predictive control of an electromagnetic suspension system based on locally linear model tree and subset selection

A predictive control algorithm based on locally linear model tree (LOLIMOT) is implemented to control of an electromagnetic suspension system. The controller uses a LOLIMOT identifier to predict the response of the plant in a future time interval. Furthermore, a subset selection technique based on the orthogonal least squares (OLS) algorithm is applied for an automatic determination of the model orders and dead times. An evolutionary programming (EP) is used to determine the optimized control variables for a finite future time interval. Simulation results on EMS system conform the effectiveness of the proposed predictive control strategy