Abstract:A bearingless induction motor is a multi-variable, nonlinear and strong-coupled system. The cross-coupled relation exists among speed and radial forces. In order to realize the rotor suspending and the motor working steadily, it is necessary to realize dynamic decoupling control among speed and radial forces. In this paper, a novel decoupling control method based on neural networks inverse system is proposed for bearingless induction motors. Theoretical analysis shows that by using the proposed method the system is decoupled into two independent linear displacement subsystems, an independent linear rotor speed subsystem and an independent linear magnetic linkage subsystem. The design of outer controllers becomes easier, and the whole system control performance is further improved. At last, taking bearingless induction motor system which adapts the proposed method as object, the study of simulation and primary experiment are done. The validity of the proposed method is proved by the simulation and primary experiment results.
孙晓东, 朱滉秋. 基于神经网络逆系统理论无轴承异步电动机解耦控制[J]. 电工技术学报, 2010, 25(1): 43-49.
Sun Xiaodong, Zhu Huangqiu. Decoupling Control of Bearingless Induction Motors Based on Neural Network Inverse System Method. Transactions of China Electrotechnical Society, 2010, 25(1): 43-49.
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