2019-08-022019-08-022019-05Rouzbehi, K., Miranian, A., Escaño González, J.M., Rakhshani, E., Shariati, N. y Pouresmaeil, E. (2019). A Data-Driven Based Voltage Control Strategy for DC-DC Converters: Application to DC Microgrid. Electronics (Switzerland), 8 (5), Article nº 493.2079-9292https://hdl.handle.net/11441/88281This 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.application/pdfengAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/DC-DC power converterTakagi–Sugeno fuzzy systemHierarchical binary treeinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess10.3390/electronics8050493