16 citations · 22 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
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…
Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution
Johan Kon, Marcel Heertjes, Tom Oomen
An increasing trend in the use of neural networks in control systems is being observed. The aim of this paper is to reveal that the straightforward application of learning neural n…
Physics-Guided Neural Networks for Feedforward Control: An Orthogonal Projection-Based Approach
Johan Kon, Dennis Bruijnen, Jeroen van de Wijdeven +2
Unknown nonlinear dynamics can limit the performance of model-based feedforward control. The aim of this paper is to develop a feedforward control framework for systems with unknow…