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The design of a position-based repetitive control for speed ripple reduction in PMLSMs

Tang, Mi; Formentini, Andrea; Odhano, Shafiq A.; Zanchetta, Pericle

Authors

MI TANG Mi.Tang@nottingham.ac.uk
Research Fellow

Andrea Formentini ezzaf1@exmail.nottingham.ac.uk

Shafiq A. Odhano



Abstract

Periodic speed errors can occur in permanent magnet linear synchronous machines for two reasons: 1) a periodic reference signal; 2) cogging force and friction. For reducing such periodic errors, iterative learning control or repetitive control approaches, used in conjunction with more common control actions, can be strongly effective. However, the design of the stability filter, robustness filter and other parameters for a traditional repetitive controller can be a complex task and may need to be adjusted when the frequency of such periodic error varies. Existing solutions tend to develop more adaptive tuning methods for repetitive controller to enhance the whole control system. This paper shows that the performance of a traditional speed loop can be enhanced with a repetitive controller without complicating the tuning of the repetitive controller. Consequently, a position-based repetitive control combined with deadbeat current control method is proposed. Simulation results show that the proposed method is effective for reducing speed ripple at difference frequencies without necessarily adjusting its parameters.

Citation

Tang, M., Formentini, A., Odhano, S. A., & Zanchetta, P. (2017). The design of a position-based repetitive control for speed ripple reduction in PMLSMs. https://doi.org/10.1109/IECON.2017.8216626

Conference Name IECON 2017 43rd Annual Conference of the IEEE Industrial Electronics Society
End Date Nov 1, 2017
Acceptance Date Jul 15, 2017
Publication Date Dec 18, 2017
Deposit Date Mar 21, 2018
Publicly Available Date Mar 21, 2018
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1109/IECON.2017.8216626
Keywords repetitive control, deadbeat control, speed ripple
reduction, permanent magnet linear synchronous machine
Public URL http://eprints.nottingham.ac.uk/id/eprint/50571
Publisher URL http://ieeexplore.ieee.org/abstract/document/8216626/
Related Public URLs http://iecon2017.csp.escience.cn/dct/page/1
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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