Rotor Unbalanced Vibration Control of Active Magnetic Bearing High-Speed Motor via Adaptive Fuzzy Controller Based on Switching Notch Filter

This paper proposes an adaptive fuzzy controller based on a switching notch filter to address the rotor unbalance vibration control problem of an active magnetic bearing (AMB) high-speed motor system in the full rotational speed range. Aiming at the complex nonlinear and time-varying characteristics of the AMB rigid rotor system, this study designs an adaptive fuzzy controller (AFC) that obtains fuzzy quantities by blurring the rotor vibration information and vibration rate of change as the input signals and then obtains the fuzzy set through fuzzy reasoning and modifies the parameters of the initial fuzzy controller. The initial fuzzy controller parameters are modified through fuzzy reasoning to improve the control effect and ensure the stable suspension of the rotor during high-speed rotation. At the same time, in order to effectively suppress the vibration of the rotor in high-speed operation due to unbalance and other factors, this paper introduces an adapting notch filter (ANF) as a vibration control strategy on the basis of AFC, and the notch filter is able to monitor the rotor vibration signals and adaptively adjust the center frequency and bandwidth. Finally, the correctness and effectiveness of the adaptive fuzzy controller based on a switching notch filter (AFC-ANF) are verified via simulations and experiments. The simulation results demonstrate that compared to traditional PID control, the AFC reduces the response time by 0.11 s. Under constant-speed operating conditions, the AFC-ANF strategy decreases rotor vibration by 60%, while under variable-speed conditions, it reduces rotor vibration displacement by 40%, showcasing significant vibration suppression effectiveness. This research provides a novel solution for vibration control in magnetic bearing systems, offering both important theoretical significance and practical application value.