activity
20182025
most citedMultivariable Iterative Learning Control Design Procedures: from Decentralized to Centralized, Illustrated on an Industrial Printer

48 citations · 69 across the 12 of their papers we have counts for

collaborators

12 papers

eess.SY2025

Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors

Max van Meer, Marijn van Noije, Koen Tiels +4

Linear Hall sensors are a cost-effective alternative to optical encoders for measuring the rotor positions of actuators, with the main challenge being that they exhibit position-de…

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.SY2025★ 2 cited

Performance Analysis of Multirate Systems: A Direct Frequency-Domain Identification Approach

Max van Haren, Lennart Blanken, Tom Oomen

Frequency-domain performance analysis of intersample behavior in sampled-data and multirate systems is challenging due to the lack of a frequency-separation principle, and systemat…

eess.SY2025

Parameter-Varying Feedforward Control: A Kernel-Based Learning Approach

Max van Haren, Lennart Blanken, Tom Oomen

The increasing demands for high accuracy in mechatronic systems necessitate the incorporation of parameter variations in feedforward control. The aim of this paper is to develop a…

eess.SY2025★ 6 cited

Lifted Frequency-Domain Identification of Closed-Loop Multirate Systems: Applied to Dual-Stage Actuator Hard Disk Drives

Max van Haren, Masahiro Mae, Lennart Blanken +1

Frequency-domain representations are crucial for the design and performance evaluation of controllers in multirate systems, specifically to address intersample performance. The aim…

eess.SY2024

Bayesian grey-box identification of nonlinear convection effects in heat transfer dynamics

Wouter M. Kouw, Caspar Gruijthuijsen, Lennart Blanken +2

We propose a computational procedure for identifying convection in heat transfer dynamics. The procedure is based on a Gaussian process latent force model, consisting of a white-bo…

eess.SY2024

A Frequency-Domain Approach for Enhanced Performance and Task Flexibility in Finite-Time ILC

Max van Haren, Kentaro Tsurumoto, Masahiro Mae +3

Iterative learning control (ILC) is capable of improving the tracking performance of repetitive control systems by utilizing data from past iterations. The aim of this paper is to…

eess.SY2023★ 8 cited

Beyond Nyquist in Frequency Response Function Identification: Applied to Slow-Sampled Systems

Max van Haren, Leonid Mirkin, Lennart Blanken +1

Fast-sampled models are essential for control design, e.g., to address intersample behavior. The aim of this paper is to develop a non-parametric identification technique for fast-…

eess.SY2023★ 2 cited

A Kernel-Based Identification Approach to LPV Feedforward: With Application to Motion Systems

Max van Haren, Lennart Blanken, Tom Oomen

The increasing demands for motion control result in a situation where Linear Parameter-Varying (LPV) dynamics have to be taken into account. Inverse-model feedforward control for L…

eess.SY2022

Basis Function feedforward for Position-Dependent Systems

Max van Haren, Lennart Blanken, Tom Oomen

Feedforward for motion systems is getting increasingly more important to achieve performance requirements. This leads to a situation where position-dependent effects cannot be negl…

eess.SY2022★ 3 cited

Frequency Domain Identification of Multirate Systems: A Lifted Local Polynomial Modeling Approach

Max van Haren, Lennart Blanken, Tom Oomen

Frequency-domain representations of multirate systems are essential for controller design and performance evaluation of multirate systems and sampled-data control. The aim of this…

eess.SY2018★ 48 cited

Multivariable Iterative Learning Control Design Procedures: from Decentralized to Centralized, Illustrated on an Industrial Printer

Lennart Blanken, Tom Oomen

Iterative Learning Control (ILC) enables high control performance through learning from measured data, using only limited model knowledge in the form of a nominal parametric model.…