On data-driven control design for non-minimum-phase plants: A comparative view

On data-driven control design for non-minimum-phase plants: A comparative view

The paper provides a comparison between noniterative direct data-driven control design approaches for non-minimum-phase systems. In particular, the most well known methods, i.e., Correlation based Tuning and Virtual Reference Feedback Tuning, are compared to the recently introduced non-iterative ver...

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Bibliographic Details
Published in:2016 IEEE 55th Conference on Decision and Control (CDC) pp. 7159 - 7164
Main Authors: Rallo, Gianmarco, Formentin, Simone, Savaresi, Sergio M.
Format: Conference Proceeding
Language:English
Published: IEEE 01-12-2016
Subjects:
Correlation
Data models
Minimization
Optimization
Stability criteria
Tuning
Online Access:Get full text
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Summary:The paper provides a comparison between noniterative direct data-driven control design approaches for non-minimum-phase systems. In particular, the most well known methods, i.e., Correlation based Tuning and Virtual Reference Feedback Tuning, are compared to the recently introduced non-iterative version of the Unfalsified Approach for control system design. The overall comparative analysis is substantiated by a thorough simulation campaign on two benchmark problems.
DOI:10.1109/CDC.2016.7799373