A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid

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Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2019-05-01

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en

Pages

14

Series

Electronics, Volume 8, issue 5

Abstract

This paper develops a data-driven strategy for identification and voltage control for DC-DC power converters. The proposed strategy does not require a pre-defined standard model of the power converters and only relies on power converter measurement data, including sampled output voltage and the duty ratio to identify a valid dynamic model for them over their operating regime. To derive the power converter model from the measurements, a local model network (LMN) is used, which is able to describe converter dynamics through some locally active linear sub-models, individually responsible for representing a particular operating regime of the power converters. Later, a local linear controller is established considering the identified LMN to generate the control signal (i.e., duty ratio) for the power converters. Simulation results for a stand-alone boost converter as well as a bidirectional converter in a test DC microgrid demonstrate merit and satisfactory performance of the proposed data-driven identification and control strategy. Moreover, comparisons to a conventional proportional-integral (PI) controllers demonstrate the merits of the proposed approach.

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Keywords

DC-DC power converter, Takagi-Sugeno fuzzy system, hierarchical bibary tree

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Citation

Rouzbehi, K, Miranian, A, Escaño, J M, Rakhshani, E, Shariati, N & Pouresmaeil, E 2019, ' A Data-Driven Based Voltage Control Strategy for DC-DC Converters : Application to DC Microgrid ', Electronics, vol. 8, no. 5, 493 . https://doi.org/10.3390/electronics8050493