Data-Driven Approach for Current Control in DC-DC Boost Converters

Chrystian Remes1, Gustavo R. Gonçalves Da Silva2, Alex Treviso2, Marcos Antonio Jeremias Coelho3, Luciola Campestrini4

  • 1Universidade Federal do Rio Grande do Sul - UFRGS
  • 2Federal University of Rio Grande do Sul
  • 3Universidade Federal do Rio Grande do Sul
  • 4Univ of Rio Grande do Sul

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Poster Session

Sessions

11:45 - 12:20 | Wed 24 Apr | Fauna | WeS2

Poster B

09:00 - 10:20 | Thu 25 Apr | Hallway | ThSS

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Abstract

This work addresses the control of the inductor current in DC-DC boost converter using a data-driven approach. Model-based approaches tend to be either conservative or complex tasks when considering intrinsic non-linearities. In that sense, data-driven solutions to the control design of such processes come in handy as they do not need a plant model and, given a sufficient rich experiment, all information needed from the system at a given operation point is obtained from data. Even for a specific data-driven method - in this work, the Virtual Reference Feedback Tuning (VRFT) - there are different ways to implement it, which allow tuning of different controller structures. In this work, we compare and apply these approaches on the control of the inductor current in a DC-DC boost converter directly on an actual plant and show that, for this kind of plant, the VRFT approach in which the inverse of the controller is identified along with the "derivative" pole outperforms the standard one.

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