68 citations · 234 across the 34 of their papers we have counts for
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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…
Unifying Model-Based and Neural Network Feedforward: Physics-Guided Neural Networks with Linear Autoregressive Dynamics
Johan Kon, Dennis Bruijnen, Jeroen van de Wijdeven +2
Unknown nonlinear dynamics often limit the tracking performance of feedforward control. The aim of this paper is to develop a feedforward control framework that can compensate thes…
Feedforward Control in the Presence of Input Nonlinearities: A Learning-based Approach
Jilles van Hulst, Maurice Poot, Dragan Kostić +3
Advanced feedforward control methods enable mechatronic systems to perform varying motion tasks with extreme accuracy and throughput. The aim of this paper is to develop a data-dri…
Optimal Commutation for Switched Reluctance Motors using Gaussian Process Regression
Max van Meer, Gert Witvoet, Tom Oomen
Switched reluctance motors are appealing because they are inexpensive in both construction and maintenance. The aim of this paper is to develop a commutation function that lineariz…
Data-enabled predictive control with instrumental variables: the direct equivalence with subspace predictive control
Jan-Willem van Wingerden, Sebastiaan Mulders, Rogier Dinkla +2
Direct data-driven control has attracted substantial interest since it enables optimization-based control without the need for a parametric model. This paper presents a new Instrum…
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…