11 citations · 29 across the 18 of their papers we have counts for
21 papers · 1 filter
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-…
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…
Identifying Lebesgue-sampled Continuous-time Impulse Response Models: A Kernel-based Approach
Rodrigo A. González, Koen Tiels, Tom Oomen
Control applications are increasingly sampled non-equidistantly in time, including in motion control, networked control, resource-aware control, and event-triggered control. Some o…
Cascaded Calibration of Mechatronic Systems via Bayesian Inference
Max van Meer, Emre Deniz, Gert Witvoet +1
Sensors in high-precision mechatronic systems require accurate calibration, which is achieved using test beds that, in turn, require even more accurate calibration. The aim of this…
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…
Learning for Precision Motion of an Interventional X-ray System: Add-on Physics-Guided Neural Network Feedforward Control
Johan Kon, Naomi de Vos, Dennis Bruijnen +3
Tracking performance of physical-model-based feedforward control for interventional X-ray systems is limited by hard-to-model parasitic nonlinear dynamics, such as cable forces and…