Iterative Robust Experiment Design for MIMO System Identification via the S-Lemma

Conference Paper (2023)
Author(s)

Nic Dirkx (Eindhoven University of Technology, ASML)

Koen Tiels (Eindhoven University of Technology)

Tom Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)

Research Group
Team Jan-Willem van Wingerden
Copyright
© 2023 Nic Dirkx, Koen Tiels, T.A.E. Oomen
DOI related publication
https://doi.org/10.1109/CCTA54093.2023.10252362
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Nic Dirkx, Koen Tiels, T.A.E. Oomen
Research Group
Team Jan-Willem van Wingerden
Pages (from-to)
998-1003
ISBN (electronic)
979-8-3503-3544-6
Reuse Rights

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Abstract

Optimal input design plays an important role in system identification for complex and multivariable systems. A known paradox in input design is that the optimal inputs depend on the true but unknown system. The aim of this paper is to design inputs for multivariable systems that are robust to all system variations within a given continuous uncertainty set. In the presented approach, the robust design problem is cast as an infinite-dimensional min-max optimization problem, and tackled via the S-lemma in an iterative approximation scheme. Experimental results from a multivariable motion system show that the algorithm enables significant robustness improvements.

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