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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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12 papers · 1 filter

eess.SY2026

Closed-loop Optimal Fault Detection for Uncertain Systems

Koen Classens, Tjeerd Ickenroth, Jeroen van de Wijdeven +1

Faults compromise the reliability and safety of complex engineering systems. The aim of this article is to address the problem of robust fault detection filter design for continuou…

eess.SY2026

Nullspace-based Fault Diagnosis for Closed-Loop Mechatronic Systems with Application to Semiconductor Equipment

Koen Classens, Jeroen van de Wijdeven, Maurice Heemels +1

Fault detection and isolation (FDI) systems are critical for modern mechatronic production equipment, as their continuous operation is heavily dependent on the ability to detect an…

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.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…

eess.SY2024

Statistical Analysis of Block Coordinate Descent Algorithms for Linear Continuous-time System Identification

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

Block coordinate descent is an optimization technique that is used for estimating multi-input single-output (MISO) continuous-time models, as well as single-input single output (SI…

eess.SY2024★ 1 cited

Identification of Additive Continuous-time Systems in Open and Closed loop

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

When identifying electrical, mechanical, or biological systems, parametric continuous-time identification methods can lead to interpretable and parsimonious models when the model s…

eess.SY2023

Direct Shaping of Minimum and Maximum Singular Values: An Synthesis Approach for Fault Detection Filters

Koen Classens, W. P. M. H. Heemels, Tom Oomen

The performance of fault detection filters relies on a high sensitivity to faults and a low sensitivity to disturbances. The aim of this paper is to develop an approach to directly…

eess.SY2022

Cross-Coupled Iterative Learning Control for Complex Systems: A Monotonically Convergent and Computationally Efficient Approach

Leontine Aarnoudse, Johan Kon, Koen Classens +5

Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. Th…

eess.SY2022★ 4 cited

Feedback linearisation of mechanical systems using data-driven models

Merijn Floren, Koen Classens, Tom Oomen +1

Linearising the dynamics of nonlinear mechanical systems is an important and open research area. A common approach is feedback linearisation, which is a nonlinear control method th…