Autobalancing of high-speed rotors suspended by magnetic bearings using LMS adaptive feedforward compensation

To suppress unbalanced vibrations of low-speed rotors suspended by magnetic bearings, such as a magnetically suspended flywheel, an autobalancing control method based on elimination of synchronous force has been applied. But its precision may decrease for high-speed rotors such as magnetically suspended control moment gyros. The reason is that the low-pass characteristic of an amplifier in a magnetic bearing control system causes errors in the force elimination. Moreover, this low-pass characteristic increases with rotational speed. To resolve this problem, we propose an autobalancing control scheme using adaptive feedforward compensation based on a least mean square (LMS) algorithm. In this LMS algorithm, two input signals are synchronous displacement and its orthogonal signal. The weights of the input signals are introduced into the algorithm. They are updated in the principle of least mean square to minimize the error between actual and reference values of synchronous current. In simulation and experiments, this method reduces synchronous vibration to less than 40% of that with conventional proportional feedforward. The results demonstrate that this method counteracts the negative effect of low-pass characteristics of an amplifier adaptively and suppresses the synchronous vibration force more precisely. Accordingly, high-precision autobalancing of high-speed rotors can be achieved.