237 citations · 553 across the 25 of their papers we have counts for
5 papers · 1 filter
A computationally lightweight safe learning algorithm
Dominik Baumann, Krzysztof Kowalczyk, Koen Tiels +1
Safety is an essential asset when learning control policies for physical systems, as violating safety constraints during training can lead to expensive hardware damage. In response…
Neural oscillators for magnetic hysteresis modeling
Abhishek Chandra, Taniya Kapoor, Bram Daniels +4
Hysteresis is a ubiquitous phenomenon in science and engineering; its modeling and identification are crucial for understanding and optimizing the behavior of various systems. We d…
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…
Kernel-based identification using Lebesgue-sampled data
Rodrigo A. González, Koen Tiels, Tom Oomen
Sampling in control applications is increasingly done non-equidistantly in time. This includes applications in motion control, networked control, resource-aware control, and event-…
Discovery of sparse hysteresis models for piezoelectric materials
Abhishek Chandra, Bram Daniels, Mitrofan Curti +3
This article presents an approach for modelling hysteresis in piezoelectric materials, that leverages recent advancements in machine learning, particularly in sparse-regression tec…