DocumentCode :
142177
Title :
Tension control improvement in automatic stator in-slot winding machines using iterative learning control
Author :
Jie-Shiou Lu ; Hung-Ruey Chen ; Ming-Yang Cheng ; Ke-Han Su ; Li-Wei Cheng ; Mi-Ching Tsai
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume :
3
fYear :
2014
fDate :
26-28 April 2014
Firstpage :
1643
Lastpage :
1647
Abstract :
Conventional motor winding machines use a passive device such as a dancer arm or hysteresis brake to adjust the tension of the wire. However, when the winding speed increases, the passive device may not be able to react quickly enough so that a sudden change in the tension will likely cause the enameled wire to vibrate. Consequently, the motor winding quality will be affected. In order to cope with this difficulty, instead of using a passive device, this paper proposes an active tension control scheme, in which the wire tension measured by a load cell is used as the feedback signal of the tension control loop. Moreover, feedforward control and iterative learning control are integrated into the proposed tension control scheme to improve system response and suppress the periodic disturbance arising from the winding process. Several motor winding experiments have been conducted to assess the performance of the proposed approach.
Keywords :
adaptive control; feedback; iterative methods; learning systems; machine control; machine windings; active tension control improvement; automatic stator in-slot winding machines; feedback signal; feedforward control; iterative learning control; periodic disturbance suppression; tension control loop; winding process; wire tension; Educational institutions; Feedback control; Feedforward neural networks; Hysteresis motors; Process control; Windings; Wires; automatic motor winding; iterative learning control; tension control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
Type :
conf
DOI :
10.1109/InfoSEEE.2014.6946200
Filename :
6946200
Link To Document :
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