Optimised sensor configurations for a Maglev suspension

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.