Optimizing PID Controller Design for Rotor Systems Suspended by Active Magnetic Bearings

Abstract

In many industrial applications, one of the primary advantages of using PID-based controllers is their simplicity, tunability, and ease of implementation. However, in the case of high-speed machines with magnetically suspended rotor systems, the stabilizing control solution often involves combining PID controllers with supporting filter structures. Depending on the case, this can lead to controllers with a significant number of tunable parameters, ranging from 10 to 35, which can be a challenging task when done manually. Therefore, a multiobjective genetic algorithm optimization is proposed in this paper to seek an optimal configuration for the controller parameters. This paper concentrates on optimizing PID-based controllers for AMB-suspended rotor systems, aiming to enable the analysis of outcomes within a standardized framework. Thus, the closed-loop performance is evaluated by the obtained damping properties and robustness. Moreover, an experimental AMB-rotor system is used to assess the performance of the controllers.