Learning, Identification and Control of High-Tech Systems

We develop methods to control real machines to the limits of performance by learning from data.

We develop methods to control real machines to the limits of performance by learning from data. Our key application domain involves the development of advanced motion control solutions for precision mechatronics. Driven by the challenges occurring in future precision mechatronics, our research focusses on fundamental issues arising in learning to control complex dynamical systems from data with robustness guarantees. As such, it is primarily positioned in the field of system identification and control, intersecting with machine learning, artificial intelligence and mechatronics. Applications are broadly addressed through collaborations with many companies and institutions in mechatronics, ranging from semiconductor equipment and printing to space and astronomy. Collaborations include ASML, Canon Production Printing, ASMPT, Thermo Fisher Scientific, TNO, Sioux, and many leading SMEs.