Data-Driven LQR Control Design

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

doi:10.1109/LCSYS.2018.2868183

Data-Driven LQR Control Design

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

Research output: Contribution to journal › Article › Academic › peer-review

36 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 language	English
Article number	8453019
Pages (from-to)	180-185
Number of pages	6
Journal	IEEE Control Systems Letters
Volume	3
Issue number	1
DOIs	https://doi.org/10.1109/LCSYS.2018.2868183
Publication status	Published - Jan 2019
Externally published	Yes

Keywords

Data-driven control
LQR control
Markov parameters
observability matrix

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10.1109/LCSYS.2018.2868183

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Data-Driven LQR Control Design

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Keywords

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