Disturbance Estimation Based Robust Model Predictive Position Tracking Control for Magnetic Levitation System

To improve the tracking performance of a magnetic levitation system in the presence of time-varying disturbances, a model predictive control (IEIDO-based MPC) scheme based on improved equivalent input disturbance observer is proposed in this paper. In order to enhance the accuracy of observer estimation, an IEIDO which can estimate both system state and time-varying equivalent input disturbance is proposed. The estimations of IEIDO are combined into the MPC design to predict the output position. Following this, an explicit analytical form of the optimal predictive controller is calculated to reduces the computational burden in practical applications, as well as the robustness against lumped input disturbance. Stability analysis shows that the closed-loop system is asymptotically stable and results of simulations show the effectiveness of the proposed method, less fluctuation of position compared with the conventional EID approach and Luenberger observer based integral MPC (LO-based IMPC).