Data-driven generalized minimum variance regulatory control using routine operation data

DOI10.1002/asjc.2776MaRDI QIDQ6580791

Ryota Uematsu, Shiro Masuda

Publication date: 30 July 2024

Published in: Asian Journal of Control (Search for Journal in Brave)

zbMATH Keywords

regulatory controlgeneralized minimum variance controldata-driven controller design

Mathematics Subject Classification ID

Systems theory; control (93-XX)

Cites Work

• Virtual reference feedback tuning for non-minimum phase plants
• Data-driven controller design. The \(H_2\) approach.
• Theory and applications of selftuning regulators
• Virtual reference feedback tuning: A direct method for the design of feedback controllers
• Controller performance benchmarking and tuning using generalised minimum variance control
• Deterministic continuous-time virtual reference feedback tuning (VRFT) with application to PID design
• Direct data-driven control of linear time-delay systems
• Virtual reference feedback tuning for two degree of freedom controllers
• Iterative correlation‐based controller tuning
• Design and Experimental Evaluation of a Discrete‐time ASPR‐based Adaptive Output Feedback Control System Using FRIT
• Direct Nonlinear Control Design: The Virtual Reference Feedback Tuning (VRFT) Approach

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