Connecting system identification and robust control for next-generation motion control of a wafer stage T Oomen, R Van Herpen, S Quist, M Van De Wal, O Bosgra, M Steinbuch
IEEE Transactions on Control Systems Technology 22 (1), 102-118, 2013
221 2013 On inversion-based approaches for feedforward and ILC J van Zundert, T Oomen
Mechatronics 50, 282-291, 2018
166 2018 Advanced motion control for precision mechatronics: Control, identification, and learning of complex systems T Oomen
IEEJ Journal of Industry Applications 7 (2), 127-140, 2018
157 2018 Rational basis functions in iterative learning control—with experimental verification on a motion system J Bolder, T Oomen
IEEE Transactions on Control Systems Technology 23 (2), 722-729, 2014
149 2014 Constrained iterative feedback tuning for robust control of a wafer stage system MF Heertjes, B Van der Velden, T Oomen
IEEE transactions on control systems technology 24 (1), 56-66, 2015
122 2015 Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification F Boeren, T Oomen, M Steinbuch
Control Engineering Practice 37, 11-19, 2015
119 2015 Frequency-domain ILC approach for repeating and varying tasks: With application to semiconductor bonding equipment F Boeren, A Bareja, T Kok, T Oomen
IEEE/ASME Transactions on Mechatronics 21 (6), 2716-2727, 2016
107 2016 Batch-to-batch rational feedforward control: from iterative learning to identification approaches, with application to a wafer stage L Blanken, F Boeren, D Bruijnen, T Oomen
IEEE/ASME Transactions on Mechatronics 22 (2), 826-837, 2016
104 2016 Optimality and flexibility in iterative learning control for varying tasks J Van Zundert, J Bolder, T Oomen
Automatica 67, 295-302, 2016
100 2016 Using iterative learning control with basis functions to compensate medium deformation in a wide-format inkjet printer J Bolder, T Oomen, S Koekebakker, M Steinbuch
Mechatronics 24 (8), 944-953, 2014
99 2014 Joint input shaping and feedforward for point-to-point motion: Automated tuning for an industrial nanopositioning system F Boeren, D Bruijnen, N van Dijk, T Oomen
Mechatronics 24 (6), 572-581, 2014
92 2014 Iterative Data-Driven T Oomen, R van der Maas, CR Rojas, H Hjalmarsson
IEEE Transactions on Control Systems Technology 22 (6), 2247-2260, 2014
80 2014 Resource-efficient ILC for LTI/LTV systems through LQ tracking and stable inversion: Enabling large feedforward tasks on a position-dependent printer J van Zundert, J Bolder, S Koekebakker, T Oomen
Mechatronics 38, 76-90, 2016
78 2016 Exploiting additional actuators and sensors for nano-positioning robust motion control R van Herpen, T Oomen, E Kikken, M van de Wal, W Aangenent, ...
Mechatronics 24 (6), 619-631, 2014
77 2014 Sparse iterative learning control with application to a wafer stage: Achieving performance, resource efficiency, and task flexibility T Oomen, CR Rojas
Mechatronics 47, 134-147, 2017
74 2017 Data‐driven multivariable ILC: enhanced performance by eliminating L and Q filters J Bolder, S Kleinendorst, T Oomen
International Journal of Robust and Nonlinear Control 28 (12), 3728-3751, 2018
72 2018 Enhancing flatbed printer accuracy and throughput: Optimal rational feedforward controller tuning via iterative learning control J Bolder, J van Zundert, S Koekebakker, T Oomen
IEEE Transactions on Industrial Electronics 64 (5), 4207-4216, 2016
59 2016 Kernel-based identification of non-causal systems with application to inverse model control L Blanken, T Oomen
Automatica 114, 108830, 2020
57 2020 Mitigation of torsional vibrations in drilling systems: A robust control approach T Vromen, CH Dai, N van de Wouw, T Oomen, P Astrid, A Doris, ...
IEEE Transactions on Control Systems Technology 27 (1), 249-265, 2017
57 2017 Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines ST Navalkar, JW van Wingerden, E van Solingen, T Oomen, ...
Mechatronics 24 (8), 916-925, 2014
57 2014 
Maarten SteinbuchEindhoven University of TechnologyEmail verificata su tue.nl
