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Dynamically Weighted Optimal Switching Vector Model Predictive Control of Power Converters

Caseiro, L. ; Mendes, A. M. S. ; Cruz, S. M. A.

IEEE Transactions on Industrial Electronics Vol. 66, Nº 2, pp. 1235 - 1245, February, 2019.

ISSN (print): 0278-0046
ISSN (online):

Scimago Journal Ranking: 2,91 (in 2019)

Digital Object Identifier: 10.1109/TIE.2018.2829689

In this paper, new techniques are presented to improve the performance of the optimal switching vector model predictive control. A well-defined analytic technique is proposed for the real-time adjustment of dynamic weighting factors, as well as a new objective function formulation. These techniques provide a dynamic controller behavior, automatically adapted to distinct operating points. This ensures better steady-state performance in different conditions while improving simultaneously the dynamic response. The proposed controller presents a lower computational load than the conventional formulation and its design requires less extensive testing. General guidelines are presented to guide the user in the controller design. Simulation and experimental results are presented, demonstrating the advantages and superior performance of the proposed controller.