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