DocumentCode :
2882739
Title :
Position based iterative learning control to minimise torque ripple for PMSMs
Author :
Yeo, Kheng Cher ; Heins, Greg ; De Boer, Friso
Author_Institution :
Charles Darwin Univ., Darwin, NT, Australia
fYear :
2011
fDate :
7-10 Nov. 2011
Firstpage :
4727
Lastpage :
4732
Abstract :
Torque ripple minimisation is achieved by an adaptive feedforward control for mass produced permanent magnet synchronous motors. Torque ripple, a major problem for such motors can be reduced using appropriate estimation scheme from speed information. The proposed method employs online zero phase filtering which can effectively minimise all torque harmonics at low speed operation. Experimental results validate the proposed scheme reducing the torque ripple factor from 6.87% to 1.28% using the proposed method. The adaptation scheme make use of PD type iterative learning control scheme which has the advantage of fast convergence compared to the more commonly used P type iterative learning control. The PD-ILC scheme is also quite robust to an initial error in the estimation of the parameter J.
Keywords :
PD control; adaptive control; feedforward; harmonics suppression; iterative methods; learning (artificial intelligence); permanent magnet motors; position control; robust control; synchronous motors; torque control; PD control; PD-ILC scheme; PMSM; adaptive feedforward control; harmonic suppression; iterative learning control; online zero phase filtering; parameter estimation; permanent magnet synchronous motors; position control; robust control; torque ripple factor; torque ripple minimisation; Estimation; Forging; Measurement uncertainty; Permanent magnet motors; Reluctance motors; Stators; Torque;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IECON 2011 - 37th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Melbourne, VIC
ISSN :
1553-572X
Print_ISBN :
978-1-61284-969-0
Type :
conf
DOI :
10.1109/IECON.2011.6119995
Filename :
6119995
Link To Document :
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