Precision motion control of permanent magnet linear motors
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In the paper, a method of precision motion control for permanent magnet linear motors is proposed. Unlike rotational motors, permanent magnetic linear motors are more sensitive to various force disturbances because of the reduction of gears. So, as a feedback compensator, a disturbance observer is used to compensate the force disturbances based on the disturbance model. But the force disturbances of permanent magnetic linear motors cannot be fully compensated owing to the error of dynamic model, inaccurately detected velocity and acceleration, especially when a permanent magnetic linear motor runs in low speed. Further analysis shows that the force ripple is the main force disturbance when the velocity of a PMLM is close to zero, and the disturbance model denotes that the force ripple is position dependent. In order to further suppress the force disturbances of permanent magnetic linear motors a feedforward neural network using the BP algorithm is proposed to approximate and compensate the force ripple. The experimental results show that the force ripple is efficiently alleviated and the high positioning precision can be achieved by using the proposed precision motion control method.
KeywordsBP algorithm Neural network Disturbance observer PMLM Motion control
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The work is supported by The National Science Foundation of China (NSFC) (Grant No. 60474021).
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