Stable and robust LQR design via scenario approach

DOI10.1016/j.automatica.2021.109571zbMath1478.49034arXiv2001.05795OpenAlexW3152127653MaRDI QIDQ2665078

Gianluigi Pillonetto, Aleksandr Y. Aravkin, Anna Scampicchio

Publication date: 18 November 2021

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.05795

zbMATH Keywords

optimal controlLyapunov stabilityreinforcement learningscenario approachpopulation growth modelsLinear Quadratic Regulator (LQR) design

Mathematics Subject Classification ID

Optimal feedback synthesis (49N35) Population dynamics (general) (92D25) Linear-quadratic optimal control problems (49N10)

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Uses Software

• ElemStatLearn
• RICPAC

Cites Work

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