Supervisory Fuzzy Model Control for Magnetic Levitation System

Magnetic levitation system (MLS), using the electromagnetic force to float, can effectively reduce the mechanical vibration friction and wearing loss caused by contact operation. However, the parameters in the mathematical model are related to the permanent magnet geometry, distance and the total mass of the platform. To achieve good tracking performance, a fuzzy system and the parameter identification algorithm for maglev suspension system are proposed in the paper. The proposed fuzzy model method is to establish a common fuzzy system procedure. By using the gathered data pairs, the parameters of membership functions are updated through gradient descent algorithm (GDA). In this paper, the fuzzy model system based on GDA is applied to ensure the effectiveness of tracking performance by replacing the mathematical model of MLS. Furthermore, to promote its performance under larger external disturbance, an auxiliary supervisory control effort is added. Thus, the chattering phenomenon is reduced and fast response can be obtained without degrading the tracking performance of the system dynamic. Some simulated and experimental results are provided to verify the feasibility and effectiveness of the proposed system.