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arXiv · 2504.01639

Identification of additive multivariable continuous-time systems

Maarten van der Hulst·Rodrigo González·Koen Classens·Nic Dirkx·Jeroen van de Wijdeven·Tom Oomen
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Abstract

Multivariable parametric models are critical for designing, controlling, and optimizing the performance of engineered systems. The main aim of this paper is to develop a parametric identification strategy that delivers accurate and physically relevant models of multivariable systems using time-domain data. The introduced approach adopts an additive model structure, providing a parsimonious and interpretable representation of many physical systems, and applies a refined instrumental variable-based estimation algorithm. The developed identification method enables the estimation of multivariable parametric additive models in continuous time and is applicable to both open- and closed-loop systems. The performance of the estimator is demonstrated through numerical simulations and experimentally validated on a flexible beam system.

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Maarten van der Hulst, Rodrigo González, Koen Classens, Nic Dirkx, Jeroen van de Wijdeven, Tom Oomen. 2025-06-30. Identification of additive multivariable continuous-time systems. https://doi.org/10.1109/lcsys.2025.3575179

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