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20222026
most citedFeedback linearisation of mechanical systems using data-driven models

4 citations · 7 across the 14 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

stat.ME2025

Finite Sample MIMO System Identification with Multisine Excitation: Nonparametric, Direct, and Two-step Parametric Estimators

Rodrigo A. González, Koen Classens, Cristian R. Rojas +2

Multisine excitations are widely used for identifying multi-input multi-output systems due to their periodicity, data compression properties, and control over the input spectrum. D…

eess.SY2025★ 1 cited

Structured identification of multivariable modal systems

Maarten van der Hulst, Rodrigo A. González, Koen Classens +4

Physically interpretable models are essential for next-generation industrial systems, as these representations enable effective control, support design validation, and provide a fo…

eess.SY2025

Statistically Optimal Structured Additive MIMO Continuous-time System Identification

Rodrigo A. González, Maarten van der Hulst, Koen Classens +1

Many applications in mechanical, acoustic, and electronic engineering require estimating complex dynamical models, often represented as additive multi-input multi-output (MIMO) tra…

eess.SY2025

Recursive Identification of Structured Systems: An Instrumental-Variable Approach Applied to Mechanical Systems

Koen Classens, Rodrigo A. González, Tom Oomen

Online system identification algorithms are widely used for monitoring, diagnostics and control by continuously adapting to time-varying dynamics. Typically, these algorithms consi…

eess.SP2025★ 1 cited

Identification of additive multivariable continuous-time systems

Maarten van der Hulst, Rodrigo González, Koen Classens +3

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…

eess.SY2025

Frequency domain identification for multivariable motion control systems: Applied to a prototype wafer stage

M. van der Hulst, R. A. González, K. Classens +4

Multivariable parametric models are essential for optimizing the performance of high-tech systems. The main objective of this paper is to develop an identification strategy that pr…

eess.SY2025

Local Rational Modeling for Identification Beyond the Nyquist Frequency: Applied to a Prototype Wafer Stage

Max van Haren, Lennart Blanken, Koen Classens +1

Fast-rate models are essential for control design, specifically to address intersample behavior. The aim of this paper is to develop a frequency-domain non-parametric identificatio…