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Modulated optimal model predictive control for variable speed gen-sets

Bigarelli, L.; Lidozzi, A.; Di Benedetto, M.; Solero, L.; Odhano, S.; Zanchetta, P.


L. Bigarelli

A. Lidozzi

M. Di Benedetto

L. Solero

S. Odhano


This paper investigates the DC-link voltage control of an active rectifier that is supplied by a variable speed permanent magnet synchronous generator. This configuration is commonly encountered in gearless wind energy conversion systems as well as in variable speed generating units. The proposed control strategy uses an optimal voltage vector based modulated model predictive control to achieve direct power control. The studied scheme combines the advantages of finite control set Model Predictive Control (MPC) and control techniques that use pulse width modulator. The fast dynamics of the former are obtained during large transients and constant switching frequency operation, of the latter, is ensured in steady state. At each sampling instant, all switching states are evaluated and the two adjacent states that give minimum error in the controlled variables are selected. The duty-cycle of each of these vectors is computed through linear combination and appropriately limited for over-modulation. Simulations and Co-simulation results presented in the paper show interesting results. The control strategy has been developed on an FPGA control platform and experimental results at steady state are shown, which guarantee the computational feasibility of the control strategy.

Start Date Sep 23, 2018
Publication Date Sep 23, 2018
Publisher Institute of Electrical and Electronics Engineers
Book Title 2018 IEEE Energy Conversion Congress and Exposition (ECCE)
ISBN 9781479973125
APA6 Citation Bigarelli, L., Lidozzi, A., Di Benedetto, M., Solero, L., Odhano, S., & Zanchetta, P. (2018). Modulated optimal model predictive control for variable speed gen-sets. In 2018 IEEE Energy Conversion Congress and Exposition (ECCE)doi:10.1109/ecce.2018.8558374
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Modulated Optimal Model Predictive Control For Variable Speed Gen-Sets (677 Kb)

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