Some sources of disturbance inevitably exist in magnetic bearings systems in the process of operation. This article proposes a disturbance suppression scheme for active magnetic bearings systems using an improved characteristic model-based all-coefficient adaptive control algorithm. First, the mathematical model of the magnetic bearing system is established. Then, by introducing the extended state observer into the adaptive control, the adaptive control method is improved. And the simulation of the combined control of the adaptive control and extended state observer is carried out based on mathematical model of controlled object. Simulation results demonstrate that this control method can not only adjust the control parameters online, but also estimate and compensate the disturbance in real time, which improves the control performance of the controller. Finally, the feasibility of adaptive control method with extended state observer is verified by experiments. When the sinusoidal disturbance signal is introduced at the 9000 r/min, the vibration displacement of the magnetic bearing system with the improved adaptive controller is reduced around 43%, which is in accordance with the theoretical results.
Iterative Learning Control with Extended State Observer for Telescope System
