No abstract

In order to solve the problem that the unbalance vibration caused by rotor mass eccentricity of the six-pole radial hybrid magnetic bearing (HMB) seriously affects stability and security of the system, a feed-forward compensation control strategy for rotor unbalance vibration based on fuzzy leastmean-square (LMS) algorithm is proposed. Firstly, the structure, operation principle, and mathematical model of the six-pole radial HMB are introduced, and the cause of rotor vibration is analyzed and the dynamic equation of rotor deduced. Secondly, an LMS self-adapting filter is improved by using a fuzzy inference system, and the step size of the LMS algorithm is combined with the fuzzy control theory. By using the Takagi-Sugeno (TS) fuzzy inference machine system to adjust the step size of the algorithm, the filter output can approach the unbalance vibration signal smoothly and quickly, and realize the vibration compensation of the rotor. Finally, the simulations and experiments are carried out to verify that the proposed method can not only effectively suppress the unbalance vibration of the six-pole radial HMB rotor in real time but also have good compensation accuracy. The results show that the vibration compensation effect of fuzzy LMS algorithm is better than that of fixed step size filtering algorithm.