Exploiting additional actuators and sensors for nano-positioning robust motion control. - Robbert van Herpen; Tom Oomen; Edward Kikken; Marc M. J. van de Wal; Wouter H. T. M. Aangenent; Maarten Steinbuch (ACC, 2014)

Hybrid derivative functions for identification of unknown loads and physical parameters with application on slider-crank mechanism. - Wannes De Groote; Edward Kikken; Srajan Goyal; Sofie Van Hoecke; Erik Hostens; Guillaume Crevecoeur (AIM, 2019)

Neural Network Augmented Physics Models for Systems with Partially Unknown Dynamics: Application to Slider-Crank Mechanism. - Wannes De Groote; Edward Kikken; Erik Hostens; Sofie Van Hoecke; Guillaume Crevecoeur (CoRR, 2019)

A cloud-based digital twin for monitoring of an adaptive clamping mechanism used for high performance composite machining. - Sam Weckx; Steven Robyns; Jonathan Baake; Edward Kikken; Roeland De Geest; Merwan Birem; Davy Maes (ISM, 2021)

Optimal Motion Control using Neural Networks Applied to a Slider-Crank Mechanism. - Edward Kikken; Jeroen Willems; Bruno Depraetere (CCTA, 2023)

A Clustering-Based Approach for Adaptive Control Applied to a Hybrid Electric Vehicle. - Rian Beck; Sudarsan Kumar Venkatesan; Joram Meskens; Jeroen Willems; Edward Kikken; Bruno Depraetere (ICINCO (1), 2023)

Probabilistic Physics-Augmented Neural Networks for Robust Control Applied to a Slider-Crank System. - Edward Kikken; Jeroen Willems; Rob Salaets; Erik Hostens (ICINCO (1), 2023)