Direct data-driven design of LPV controllers with soft performance specifications

DOI10.1016/J.JFRANKLIN.2021.04.052zbMath1481.93042OpenAlexW3161223798MaRDI QIDQ2071160

Simone Formentin, Tom Oomen, Valentina Breschi, Max van Meer

Publication date: 25 January 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.04.052

zbMATH Keywords

linear parameter-varying systemsfeedback controller synthesisdata-driven design

Mathematics Subject Classification ID

Feedback control (93B52) Linear systems in control theory (93C05)

Related Items (1)

Auto-tuning of reference models in direct data-driven control

Uses Software

• Matlab

Cites Work

• Unnamed Item
• Enhancing statistical performance of data-driven controller tuning via \(\mathcal{L}_2-\)regularization
• Virtual reference feedback tuning for non-minimum phase plants
• Direct learning of LPV controllers from data
• Virtual reference feedback tuning: A direct method for the design of feedback controllers
• Data-driven control of nonlinear systems: an on-line direct approach
• Data-driven model reference control with asymptotically guaranteed stability
• Data-Driven Model Predictive Control With Stability and Robustness Guarantees

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