Optimised sensor configurations for a Maglev suspension
Konstantinos Michail
Argyrios C. Zolotas
Roger Goodall
2134/3351
https://repository.lboro.ac.uk/articles/online_resource/Optimised_sensor_configurations_for_a_Maglev_suspension/9552143
This paper discusses a systematic approach for selecting the minimum number of
sensors for an Electromagnetic levitation system that satisfies both deterministic and stochastic
performance objectives. The controller tuning is based upon the utilisation of a recently
developed genetic algorithm, namely NSGAII. Two controller structures are discussed, an inner
loop classical solution for illustrating the efficacy of the NSGAII tuning and a Linear quadratic
gaussian structure particularly on sensor optimization.
2008-05-27 16:21:25
untagged
Mechanical Engineering not elsewhere classified