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Wire tension control of an automatic motor winding machinean iterative learning sliding mode control approach

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This paper focuses on active wire tension control of motor winding machines.An ILSMC scheme for wire tension control is developed.A disturbance observer is used to implement sensorless wire tension control.The… Click to show full abstract

This paper focuses on active wire tension control of motor winding machines.An ILSMC scheme for wire tension control is developed.A disturbance observer is used to implement sensorless wire tension control.The estimated wire speed is exploited in designing the tension control scheme.The stability and convergence proof of the proposed approach is provided. One of the most crucial factors that affects the winding quality in an automatic motor winding process is the regulation of wire tension. Most commercial automatic motor winding machines use passive devices such as a dancer arm or a hysteresis brake to adjust the wire tension. However, as the winding speed increases, these passive devices may not be able to react quickly enough to maintain constant wire tension and may cause the enameled wire to tremble. In order to cope with the aforementioned problems, this paper conducts an in-depth study on active wire tension control of automatic motor winding machines. In particular, an iterative learning sliding mode control scheme for wire tension control is developed in this paper, while a disturbance observer is employed to estimate the wire tension for the implementation of sensorless wire tension control. Moreover, due to the fact that the motion of the unwind roll is affected by the motion of the enameled wire, the estimated wire speed information is exploited in the design of the tension control scheme to lessen the lag phenomenon. Results of the winding experiments verify the effectiveness of the proposed wire tension control scheme.

Keywords: tension control; wire; tension; motor winding; wire tension

Journal Title: Robotics and Computer-integrated Manufacturing
Year Published: 2018

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