Robust Control Design for Maglev Train with Parametric Uncertainties Using µ-Synthesis

The magnetic suspension systems that they are basis of maglev trains divided in two classes: electrodynamic suspension (EDS) and electromagnetic suspension (EMS). EDS is based on repulsive forces acting on a magnet and is inherently stable system and even has well robustness in many cases with open loop control. But EMS is based on attractive forces acting on a magnet, is inherently unstable system that without feedback control has a poor performance. So, we must use feedback and we need to an exact mathematical model of plant to synthesis the feedback control system. This model should contain different uncertainties to make it more similar to actual model. Therefore, control system should have robust stability and performance under model uncertainties. Above desires will be accessible with a controller inμ framework. In this paper, we assume that the suspension system is EMS and perturbations of the model parameters are considered as the source of uncertainty. Since we can represent these perturbations in state space parameters (A, B, C, D) ,uncertainty will be structured.