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

Author

Mohammadzaman, Iman ; Jama, Atiye Sarabi

Author_Institution

Malek Ashlar Univ. of Technol., Tehran

fYear

0

fDate

0-0 0

Firstpage

579

Lastpage

584

Abstract

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

Keywords

evolutionary computation; fuzzy control; least squares approximations; mechanical variables control; nonlinear control systems; optimal control; predictive control; suspensions (mechanical components); trees (mathematics); electromagnetic suspension system; evolutionary programming; locally linear model tree; nonlinear predictive control; orthogonal least squares; subset selection technique; Automatic control; Electrical equipment industry; Electromagnetic modeling; Genetic programming; Industrial control; Least squares methods; Medical services; Nonlinear systems; Predictive control; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Motion Control, 2006. 9th IEEE International Workshop on

Conference_Location

Istanbul

Print_ISBN

0-7803-9511-1

Type

conf

DOI

10.1109/AMC.2006.1631724

Filename

1631724