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Recent Advances of Predictive Control in Power Converters

Perez-Guzman, Ricardo Enrique; Rivera, Marco; Wheeler, Patrick W.


Ricardo Enrique Perez-Guzman

Marco Rivera


Model-based predictive control (MPC) is an attractive solution for controlling power converters and drives. This research shows the most recent alternatives of predictive control techniques proposed in the literature to solve control problems in power converters. The current trends and future projections for these control strategies, as well as the most used models, topologies, or variables in different scenarios are shown. This allowed us to compare the main strategies, their pros and cons, including some application examples. Predictive control has several advantages that make it suitable for the control of power converters and drives.


Perez-Guzman, R. E., Rivera, M., & Wheeler, P. W. (2020). Recent Advances of Predictive Control in Power Converters. In Proceedings: 2020 IEEE International Conferenceon Industrial Technology.

Conference Name 2020 IEEE International Conference on Industrial Technology (ICIT)
Start Date Feb 26, 2020
End Date Feb 28, 2020
Acceptance Date Nov 15, 2019
Online Publication Date Apr 16, 2020
Publication Date Feb 26, 2020
Deposit Date Jul 29, 2020
Publicly Available Date Jul 31, 2020
Publisher Institute of Electrical and Electronics Engineers
Book Title Proceedings: 2020 IEEE International Conferenceon Industrial Technology
ISBN 9781728157542
Public URL
Publisher URL
Additional Information © 2020 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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