Data-Driven LQR Control Design

Gustavo R. Gonçalves da Silva, Alexandre S. Bazanella, Charles Lorenzini, Luciola Campestrini

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

Abstract

This letter presents a data-driven solution to the discrete-time infinite horizon linear quadratic regulator (LQR) problem. The state feedback gain is computed directly from a batch of input and state data collected from the plant. Simulation examples illustrate the convergence of the proposed solution to the optimal LQR gain as the number of Markov parameters tends to infinity. Experiments in an uninterruptible power supply are presented, which demonstrate the practical applicability of the design methodology.

Original languageEnglish
Article number8453019
Pages (from-to)180-185
Number of pages6
JournalIEEE Control Systems Letters
Volume3
Issue number1
DOIs
Publication statusPublished - Jan 2019
Externally publishedYes

Keywords

  • Data-driven control
  • LQR control
  • Markov parameters
  • observability matrix

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