Data-driven tuning of model-reference controllers for stable MIMO plants

DOI10.1016/J.AUTOMATICA.2021.109786zbMath1478.93309OpenAlexW3175521329MaRDI QIDQ2665423

Masami Saeki

Publication date: 19 November 2021

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2021.109786

zbMATH Keywords

least-squares methodmodel matchingproportional-integral-derivative controlvirtual reference feedback tuningdata-driven controller tuningplant step responses

Mathematics Subject Classification ID

Feedback control (93B52) Multivariable systems, multidimensional control systems (93C35)

Cites Work

• Virtual reference feedback tuning for non-minimum phase plants
• Virtual reference feedback tuning: A direct method for the design of feedback controllers
• Deterministic continuous-time virtual reference feedback tuning (VRFT) with application to PID design
• Correlation-based tuning of decoupling multivariable controllers
• Data-driven loop-shaping design of PID controllers for stable plants
• Data-driven model reference control with asymptotically guaranteed stability
• The unfalsified control concept and learning

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