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Indirect predictive control strategy with fixed switching frequency for a direct matrix converter

Rivera, Marco; Tariscotti, Luca; Wheeler, Patrick; Bayhan, S.

Authors

Marco Rivera

Luca Tariscotti

S. Bayhan



Abstract

The direct matrix converter has a large number of available switching states which implies that the implementation of predictive control techniques in this converter requires high computational cost while an adequate selection of weighting factors in order to control both input and output sides. In this paper, an indirect model predictive current control strategy is proposed in order to simplify the computational cost while avoiding the use of weighting factors. The method is based on the fictitious dc-link concept, which has been used in the past for the classical modulation and control techniques of the direct matrix converter. The proposal is enhanced with a fixed switching predictive strategy in order to improve the performance of the full system. Simulated results confirm the feasibility of the proposal demonstrating that it is an alternative to classical predictive control strategies for the direct matrix converter.

Citation

Rivera, M., Tariscotti, L., Wheeler, P., & Bayhan, S. (in press). Indirect predictive control strategy with fixed switching frequency for a direct matrix converter

Conference Name 43rd Annual Conference of the IEEE Industrial Electronics Society - IECON 2017
End Date Nov 1, 2017
Acceptance Date Jul 15, 2017
Online Publication Date Dec 18, 2017
Deposit Date Jan 18, 2018
Publicly Available Date Jan 18, 2018
Electronic ISSN 1553-572X
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/49168
Publisher URL http://ieeexplore.ieee.org/document/8217284/
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 Published in 2017 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017), Bejing, China, 29 Oct-1 Nov 2017 IEEE, 2017. ISBN: 9781538611272, pp. 7332-7337, doi:10.1109/IECON.2017.8217284

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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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