Identification of Additive Multivariable Continuous-Time Systems
Maarten Van Der Hulst (Eindhoven University of Technology)
Rodrigo A. González (Eindhoven University of Technology)
Koen Classens (Eindhoven University of Technology)
Nic Dirkx (ASML)
Jeroen van de Wijdeven (ASML)
T.A.E. Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
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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 letter 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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