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Open AccessFeature PaperArticle

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

1
Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla, 41092 Sevilla, Spain
2
Department of Electrical Engineering, University of Tehran, Tehran 1417466191, Iran
3
Department of Electrical Sustainable Energy, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands
4
Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia
5
Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(5), 493; https://doi.org/10.3390/electronics8050493
Received: 27 March 2019 / Revised: 18 April 2019 / Accepted: 22 April 2019 / Published: 30 April 2019
(This article belongs to the Special Issue Industrial Applications of Power Electronics)
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. View Full-Text
Keywords: DC-DC power converter; Takagi–Sugeno fuzzy system; hierarchical binary tree DC-DC power converter; Takagi–Sugeno fuzzy system; hierarchical binary tree
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MDPI and ACS Style

Rouzbehi, K.; Miranian, A.; Escaño, J.M.; Rakhshani, E.; Shariati, N.; Pouresmaeil, E. A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid. Electronics 2019, 8, 493. https://doi.org/10.3390/electronics8050493

AMA Style

Rouzbehi K, Miranian A, Escaño JM, Rakhshani E, Shariati N, Pouresmaeil E. A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid. Electronics. 2019; 8(5):493. https://doi.org/10.3390/electronics8050493

Chicago/Turabian Style

Rouzbehi, Kumars; Miranian, Arash; Escaño, Juan M.; Rakhshani, Elyas; Shariati, Negin; Pouresmaeil, Edris. 2019. "A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid" Electronics 8, no. 5: 493. https://doi.org/10.3390/electronics8050493

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