Vol.6, Special Issue, 2007 pp. 169-184
UDC 681.586:519.863(045)=111
OPTIMISED SENSOR CONFIGURATIONS FOR A
MAGLEV SUSPENSION SYSTEM
Konstantinos Michail, Argyrios C. Zolotas, Roger M. Goodall
Department of Electronic and Electrical Engineering, Loughborough University,
Loughborough, England, United Kingdom
e-mail: k.mihail; a.c.zolotas;
g.m.goodall @lboro.ac.uk
Abstract. This paper discusses a systematic approach for selecting
the minimum number of sensors for an Electromagnetic suspension system
that satisfies both optimised deterministic and stochastic performance
objectives. The performance is optimised by tuning the controller using
evolutionary algorithms. Two controller strategies are discussed, an inner
loop classical solution for illustrating the efficacy of the evolutionary
algorithm and a Linear Quadratic Gaussian (LQG) structure particularly
on sensor optimisation.
Key words: Sensor optimisation, MAGLEV suspensions, EMS optimisation,
genetic algorithms, Kalman filter, evolutionary algorithms
OPTIMALNA SENZORSKA KONFIGURACIJA ZA MAGLEV
LEVITACIONI SISTEM SUSPENZIJE
Ovaj rad se bavi sistematskim pristupom u odabiranju minimalnog broja senzora
za sistem elektromagnetne levitacione suspenziju koji zadovoljava obe ciljeve
determinističke i stohastičke optimalne performanse. Performansa je optimalna
podešavanjem upravljanja uz pomoć razvojnih algoritama. Proučavaju se
dve strategije upravljanja, unutrašnja petlja klasičnog rešenja za ilustraciju
efikasnosti razvojnih algoritama i Linearne Kvadratne Gausijeve (LQG) strukture
posebno za optimizaciju senzora.
Ključne reči: Optimizacija senzora, MagLev suspenzija, EMS
optimizacija, genetski algoritmi, Kalmanov filter, razvojni algoritmi
