COMPUTATIONALLY EFFICIENT ROBUST MODEL PREDICTIVE CONTROL OF MAGNETIC SUSPENSION SYSTEMS

Robust model predictive control (MPC) of a general magnetic suspension system (MSS) is analyzed. Tight positioning requirements in the presence of constraints makes MPC a promising control technique for this system. While inherent robustness of the MPC approach may be able to handle some amount of model nonlinearities and external disturbances, we consider a robust approach that systematically incorporates the effects of uncertainties and disturbances in the linearized dynamics model and explore its applicability for a range of operating points or reference inputs of the MSS. Simulation results illustrate the effectiveness and the computational simplicity of the robust MPC approach.