Frequency domain design of iterative learning control and repetitive control for complex motion systems NWA Strijbosch, LLG Blanken, TAE Oomen
4th IEEJ International Workshop on Sensing, Actuation, Motion Control, and …, 2018
23 2018 Control-relevant neural networks for intelligent motion feedforward L Aarnoudse, W Ohnishi, M Poot, P Tacx, N Strijbosch, T Oomen
2021 IEEE International Conference on Mechatronics (ICM), 1-6, 2021
20 2021 -Gain Analysis of Periodic Event-Triggered Control and Self-Triggered Control Using LiftingN Strijbosch, GE Dullerud, AR Teel, W Heemels
IEEE Transactions on Automatic Control 66 (8), 3749-3756, 2020
20 2020 Iterative learning control for intermittently sampled data: Monotonic convergence, design, and applications N Strijbosch, T Oomen
Automatica 139, 110171, 2022
16 2022 Beyond quantization in iterative learning control: Exploiting time-varying time-stamps N Strijbosch, T Oomen
2019 American Control Conference (ACC), 2984-2989, 2019
11 2019 Commutation angle iterative learning control: Enhancing piezo-stepper actuator Waveforms N Strijbosch, P Tacx, E Verschueren, T Oomen
IFAC-PapersOnLine 52 (15), 579-584, 2019
11 2019 Multirate state tracking for improving intersample behavior in iterative learning control W Ohnishi, N Strijbosch, T Oomen
2021 IEEE International Conference on Mechatronics (ICM), 01-06, 2021
9 2021 Physics-guided neural networks for feedforward control with input-to-state-stability guarantees M Bolderman, H Butler, S Koekebakker, E van Horssen, R Kamidi, ...
Control Engineering Practice 145, 105851, 2024
8 2024 State‐tracking iterative learning control in frequency domain design for improved intersample behavior W Ohnishi, N Strijbosch, T Oomen
International Journal of Robust and Nonlinear Control 33 (7), 4009-4027, 2023
8 2023 Hybrid-MEM-element feedforward: With application to hysteretic piezoelectric actuators N Strijbosch, T Oomen
2020 59th IEEE Conference on Decision and Control (CDC), 934-939, 2020
8 2020 Iterative learning control with discrete‐time nonlinear nonminimum phase models via stable inversion IA Spiegel, N Strijbosch, T Oomen, K Barton
International Journal of Robust and Nonlinear Control 31 (16), 7985-8006, 2021
7 2021 Hysteresis feedforward compensation: A direct tuning approach using hybrid-MEM-elements N Strijbosch, K Tiels, T Oomen
IEEE Control Systems Letters 6, 1070-1075, 2021
7 2021 Commutation-angle iterative learning control for intermittent data: Enhancing piezo-stepper actuator waveforms L Aarnoudse, N Strijbosch, E Verschueren, T Oomen
IFAC-PapersOnLine 53 (2), 8585-8590, 2020
7 2020 Monotonically convergent iterative learning control for piecewise affine systems N Strijbosch, I Spiegel, K Barton, T Oomen
IFAC-PapersOnLine 53 (2), 1474-1479, 2020
5 2020 Intermittent sampling in iterative learning control: a monotonically-convergent gradient-descent approach with application to time stamping N Strijbosch, T Oomen
2019 IEEE 58th Conference on Decision and Control (CDC), 6542-6547, 2019
5 2019 Multivariable iterative learning control: analysis and designs for engineering applications L Blanken, J van Zundert, R de Rozario, N Strijbosch, T Oomen
Data-driven modeling, filtering and control: methods and applications, 109-143, 2019
5 2019 Memory-Element-Based Hysteresis: Identification and Compensation of a Piezoelectric Actuator N Strijbosch, K Tiels, T Oomen
IEEE Transactions on Control Systems Technology 31 (6), 2863-2870, 2023
4 2023 High Precision Sample Positioning in Electron Microscopes N Strijbosch, E Verschueren, K Tiels, T Oomen
Mikroniek 4, 26-31, 2021
3 2021 Long-range piezo-stepper actuators: Nanoscale accuracy through commutation-angle iterative learning control LIM Aarnoudse, NWA Strijbosch, ERM Verschueren, TAE Oomen
ASPE Spring Topical Meeting 2020: Design and Control of Precision …, 2020
3 2020 Control-relevant neural networks for feedforward control with preview: Applied to an industrial flatbed printer L Aarnoudse, J Kon, W Ohnishi, M Poot, P Tacx, N Strijbosch, T Oomen
IFAC Journal of Systems and Control 27, 100241, 2024
2 2024