Exploiting H∞ Sampled-Data Control Theory for High-Precision Electromechanical Servo Control Design. - Tom Oomen; Marc M. J. van de Wal; Okko H. Bosgra (ACC, 2006)

Aliasing of Resonance Phenomena in Sampled-Data Feedback Control Design: Hazards, Modeling, and a Solution. - Tom Oomen; Marc M. J. van de Wal; Okko H. Bosgra (ACC, 2007)

Design framework for high-performance optimal sampled-data control with application to a wafer stage. - Tom Oomen; Marc M. J. van de Wal; Okko H. Bosgra (Int. J. Control, 2007)

Robust-control-relevant coprime factor identification: A numerically reliable frequency domain approach. - Tom Oomen; Okko H. Bosgra (ACC, 2008)

Estimating disturbances and model uncertainty in model validation for robust control. - Tom Oomen; Okko H. Bosgra (CDC, 2008)

Low-order system identification and optimal control of intersample behavior in ILC. - Tom Oomen; Jeroen van de Wijdeven; Okko H. Bosgra (ACC, 2009)

Reading of cracked optical discs using Iterative Learning Control. - Maarten Steinbuch; Kees van Berkel 001; George A. L. Leenknegt; Tom Oomen; Jeroen van de Wijdeven (ACC, 2009)

Identification for robust inferential control. - Tom Oomen; Okko H. Bosgra; Marc M. J. van de Wal (CDC, 2009)

Suppressing intersample behavior in iterative learning control. - Tom Oomen; Jeroen van de Wijdeven; Okko H. Bosgra (Autom., 2009)

Experimental validation of a truck roll model using asynchronous measurements with low signal-to-noise ratios. - Willem-Jan Evers; Igo Besselink; Arjan Teerhuis; Tom Oomen; Henk Nijmeijer (ACC, 2010)

Experimental evaluation of robust-control-relevance: A confrontation with a next-generation wafer stage. - Robbert van Herpen; Tom Oomen; Marc M. J. van de Wal; Okko H. Bosgra (ACC, 2010)

A robust-control-relevant model validation approach for continuously variable transmission control. - Tom Oomen; Stan van der Meulen; Okko H. Bosgra; Maarten Steinbuch; Jos Elfring (ACC, 2010)

Identification and visualization of robust-control-relevant model sets with application to an industrial wafer stage. - Tom Oomen; Sander Quist; Robbert van Herpen; Okko H. Bosgra (CDC, 2010)

A robust-control-relevant perspective on model order selection. - Robbert van Herpen; Tom Oomen; Okko H. Bosgra (ACC, 2011)

Inferential motion control: Identification and robust control with unmeasured performance variables. - Tom Oomen; Erik Grassens; Ferdinand Hendriks; Robbert van Herpen; Okko H. Bosgra (CDC/ECC, 2011)

System Identification and Low-Order Optimal Control of Intersample Behavior in ILC. - Tom Oomen; Jeroen van de Wijdeven; Okko H. Bosgra (IEEE Trans. Autom. Control., 2011)

Iterative learning control with basis functions for media positioning in scanning inkjet printers. - Joost Bolder; Bas P. Lemmen; Sjirk H. Koekebakker; Tom Oomen; Okko H. Bosgra; Maarten Steinbuch (ISIC, 2012)

Next-generation wafer stage motion control: Connecting system identification and robust control. - Tom Oomen; Robbert van Herpen; Sander Quist; Marc M. J. van de Wal; Okko H. Bosgra; Maarten Steinbuch (ACC, 2012)

Bi-orthonormal basis functions for improved frequency-domain system identification. - Robbert van Herpen; Tom Oomen; Okko H. Bosgra (CDC, 2012)

System identification for achieving robust performance. - Tom Oomen; Okko H. Bosgra (Autom., 2012)

Uniquely connecting frequency domain representations of given order polynomial Wiener-Hammerstein systems. - David Rijlaarsdam; Tom Oomen; Pieter Nuij; Johan Schoukens; Maarten Steinbuch (Autom., 2012)

Analyzing iterations in identification with application to nonparametric H∞-norm estimation. - Cristian R. Rojas; Tom Oomen; Håkan Hjalmarsson; Bo Wahlberg (Autom., 2012)

Enhancing performance through multivariable weighting function design in ℋ- loop-shaping: with application to a motion system. - Frank Boeren; Robbert van Herpen; Tom Oomen; Marc M. J. van de Wal; Okko H. Bosgra (ACC, 2013)

Iteratively learning the ℌ∞-norm of multivariable systems applied to model-error-modeling of a vibration isolation system. - Tom Oomen; Rick van der Maas; Cristian R. Rojas; Håkan Hjalmarsson (ACC, 2013)

Iterative feedforward control: a closed-loop identification problem and a solution. - Frank Boeren; Tom Oomen (CDC, 2013)

Exploiting rational basis functions in iterative learning control. - Joost Bolder; Tom Oomen; Maarten Steinbuch (CDC, 2013)

Accuracy aspects in motion feedforward tuning. - Frank Boeren; Tom Oomen; Maarten Steinbuch (ACC, 2014)

On inferential Iterative Learning Control: With example to a printing system. - Joost Bolder; Tom Oomen; Maarten Steinbuch (ACC, 2014)

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)

Subspace Predictive Repetitive Control for wind turbine load alleviation using trailing edge flaps. - Sachin Tejwant Navalkar; Jan-Willem van Wingerden; Edwin van Solingen; Tom Oomen; G. A. M. van Kuik (ACC, 2014)

Aspects in inferential Iterative Learning Control: A 2D systems analysis. - Joost Bolder; Tom Oomen; Maarten Steinbuch (CDC, 2014)

Optimally conditioned instrumental variable approach for frequency-domain system identification. - Robbert van Herpen; Tom Oomen; Maarten Steinbuch (Autom., 2014)

Controlling aliased dynamics in motion systems? An identification for sampled-data control approach. - Tom Oomen (Int. J. Control, 2014)

Connecting System Identification and Robust Control for Next-Generation Motion Control of a Wafer Stage. - Tom Oomen; Robbert van Herpen; Sander Quist; Marc M. J. van de Wal; Okko H. Bosgra; Maarten Steinbuch (IEEE Trans. Control. Syst. Technol., 2014)

Iterative Data-Driven ℋ∞ Norm Estimation of Multivariable Systems With Application to Robust Active Vibration Isolation. - Tom Oomen; Rick van der Maas; Cristian R. Rojas; Håkan Hjalmarsson (IEEE Trans. Control. Syst. Technol., 2014)

Data-driven optimal ILC for multivariable systems: Removing the need for L and Q filter design. - Joost Bolder; Tom Oomen (ACC, 2015)

Iterative Learning Control for varying tasks: Achieving optimality for rational basis functions. - Jurgen van Zundert; Joost Bolder; Tom Oomen (ACC, 2015)

Feedforward for multi-rate motion control: Enhanced performance and cost-effectiveness. - J. C. D. van Zundert; J. L. C. Verhaegh; Wouter H. T. M. Aangenent; Tom Oomen; Duarte Antunes; W. P. M. H. Heemels (ACC, 2015)

Optimal estimation of rational feedforward controllers: An instrumental variable approach. - Frank Boeren; Lennart Blanken; Dennis Bruijnen; Tom Oomen (CDC, 2015)

Unified ILC framework for repeating and varying tasks: A frequency domain approach with application to a wire-bonder. - Frank Boeren; Abhishek Bareja; Tom Kok; Tom Oomen (CDC, 2015)

Enhancing current density profile control in tokamak experiments using iterative learning control. - Federico Felici; Tom Oomen (CDC, 2015)

Accurate frequency response function identification of LPV systems: A 2D local parametric modeling approach. - Rick van der Maas; Annemiek van der Maas; Tom Oomen (CDC, 2015)

Rational Basis Functions in Iterative Learning Control - With Experimental Verification on a Motion System. - Joost Bolder; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2015)

Inferential Motion Control: Identification and Robust Control Framework for Positioning an Unmeasurable Point of Interest. - Tom Oomen; Erik Grassens; Ferdinand Hendriks (IEEE Trans. Control. Syst. Technol., 2015)

Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison. - Lennart Blanken; Frank Boeren; Dennis Bruijnen; Tom Oomen (ACC, 2016)

Frequency response function identification of LPV systems: A 2D-LRM approach with application to a medical X-ray system. - Annemiek van der Maas; Rick van der Maas; Robbert Voorhoeve; Tom Oomen (ACC, 2016)

Identification for motion control: Incorporating constraints and numerical considerations. - Robbert Voorhoeve; Robin de Rozario; Tom Oomen (ACC, 2016)

On the potential of lifted domain feedforward controllers with a periodic sampling sequence. - Jurgen van Zundert; Tom Oomen; Dip Goswami; W. P. M. H. Heemels (ACC, 2016)

Design and modeling aspects in multivariable iterative learning control. - Lennart Blanken; Sjirk H. Koekebakker; Tom Oomen (CDC, 2016)

Inferential Iterative Learning Control: A 2D-system approach. - Joost Bolder; Tom Oomen (Autom., 2016)

Optimality and flexibility in Iterative Learning Control for varying tasks. - Jurgen van Zundert; Joost Bolder; Tom Oomen (Autom., 2016)

Bi-Orthonormal Polynomial Basis Function Framework With Applications in System Identification. - Robbert van Herpen; Okko H. Bosgra; Tom Oomen (IEEE Trans. Autom. Control., 2016)

Constrained Iterative Feedback Tuning for Robust Control of a Wafer Stage System. - Marcel François Heertjes; Bart Van der Velden; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2016)

Distributed model predictive control for ink-jet 3D printing. - Yijie Guo; Joost Peters; Tom Oomen; Sandipan Mishra (AIM, 2017)

Evaluating performance of multivariable vibration isolators: A frequency domain identification approach applied to an industrial AVIS. - Michiel A. Beijen; Marcel Heertjes; Robbert Voorhoeve; Tom Oomen (ACC, 2017)

Iterative Learning Control and feedforward for LPV systems: Applied to a position-dependent motion system. - Robin de Rozario; Tom Oomen; Maarten Steinbuch (ACC, 2017)

An approach to stable inversion of LPTV systems with application to a position-dependent motion system. - Jurgen van Zundert; Tom Oomen (ACC, 2017)

Multivariable repetitive control design framework applied to flatbed printing with continuous media flow. - Lennart Blanken; Tim Hazelaar; Sjirk H. Koekebakker; Tom Oomen (CDC, 2017)

Data-driven H∞-norm estimation via expert advice. - Gianmarco Rallo; Simone Formentin; Cristian R. Rojas; Tom Oomen; Sergio M. Savaresi (CDC, 2017)

Sparse Iterative Learning Control with Application to a Wafer Stage: Achieving Performance, Resource Efficiency, and Task Flexibility. - Tom Oomen; Cristian R. Rojas (CoRR, 2017)

Enhancing feedforward controller tuning via instrumental variables: with application to nanopositioning. - Frank Boeren; Dennis Bruijnen; Tom Oomen (Int. J. Control, 2017)

Accurate FRF Identification of LPV Systems: nD-LPM With Application to a Medical X-Ray System. - Rick van der Maas; Annemiek van der Maas; Robbert Voorhoeve; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2017)

Enhancing Flatbed Printer Accuracy and Throughput: Optimal Rational Feedforward Controller Tuning Via Iterative Learning Control. - Joost Bolder; Jurgen van Zundert; Sjirk H. Koekebakker; Tom Oomen (IEEE Trans. Ind. Electron., 2017)

Kernel-based regression of non-causal systems for inverse model feedforward estimation. - Lennart Blanken; Ids van den Meijdenberg; Tom Oomen (AMC, 2018)

Sparse iterative learning control (SPILC): When to sample for resource-efficiency? - Tom Oomen; Cristian R. Rojas (AMC, 2018)

Improving transient learning behavior in model-free inversion-based iterative control with application to a desktop printer. - Robin de Rozario; Tom Oomen (AMC, 2018)

LPTV loop-shaping with application to non-equidistantly sampled precision mechatronics. - Jurgen van Zundert; Tom Oomen (AMC, 2018)

Data-Driven Feedforward Learning using Non-Causal Rational Basis Functions: Application to an Industrial Flatbed Printer. - Lennart Blanken; Goksan Isil; Sjirk H. Koekebakker; Tom Oomen (ACC, 2018)

Accommodating Trial-Varying Tasks in Iterative Learning Control for LPV Systems, Applied to Printer Sheet Positioning. - Robin de Rozario; Remy Pelzer; Sjirk H. Koekcbakker; Tom Oomen (ACC, 2018)

Achieving Perfect Causal Feedforward Control in Presence of Nonminimum-Phase Behavior - Exploiting Additional Actuators and Squaring Down. - Jurgen van Zundert; Fons Luijten; Tom Oomen (ACC, 2018)

Numerically Reliable Identification of Fast Sampled Systems: A Novel δ-Domain Data-Dependent Orthonormal Polynomial Approach. - Robbert Voorhoeve; Tom Oomen (CDC, 2018)

Thermo-Mechanical Behavior in Precision Motion Control: Unified Framework for Fast and Accurate FRF Identification. - Enzo Evers; Bram De Jager; Tom Oomen (IECON, 2018)

Identifying Position-Dependent Mechanical Systems: A Modal Approach with Applications to Wafer Stage Control. - Robbert Voorhoeve; Robin de Rozario; Wouter H. T. M. Aangenent; Tom Oomen (CoRR, 2018)

Feedforward Motion Control: From Batch-to-Batch Learning to Online Parameter Estimation. - Noud Mooren; Gert Witvoet; Tom Oomen (ACC, 2019)

Online hose calibration for pressure control in mechanical ventilation. - Joey Reinders; Frank Heck; Bram Hunnekens; Tom Oomen; Nathan van de Wouw (ACC, 2019)

Multivariable Learning Using Frequency Response Data: A Robust Iterative Inversion-Based Control Approach with Application. - Robin de Rozario; Juliana Langen; Tom Oomen (ACC, 2019)

Beyond Quantization in Iterative Learning Control: Exploiting Time-Varying Time-Stamps. - Nard Strijbosch; Tom Oomen (ACC, 2019)

Line-to-line repetitive control of a 6-DoF hexapod stage for overlay measurements using Atomic Force Microscopy. - Gert Witvoet; Joost Peters; Stefan Kuiper; Tom Oomen (ACC, 2019)

System Inversion for Sampled-Data Feedforward Control: Balancing On-Sample and Intersample Behavior. - Jurgen van Zundert; Wataru Ohnishi; Hiroshi Fujimoto; Tom Oomen (ACC, 2019)

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions. - Tom Bloemers; Roland Tóth; Tom Oomen (CDC, 2019)

Intermittent Sampling in Iterative Learning Control: a Monotonically-Convergent Gradient-Descent Approach with Application to Time Stamping. - Nard Strijbosch; Tom Oomen (CDC, 2019)

Iterative learning control in high-performance motion systems: from theory to implementation. - Martin Goubej; Sven Meeusen; Noud Mooren; Tom Oomen (ETFA, 2019)

Data-driven iterative inversion-based control: Achieving robustness through nonlinear learning. - Robin de Rozario; Tom Oomen (Autom., 2019)

Stable inversion of LPTV systems with application in position-dependent and non-equidistantly sampled systems. - Jurgen van Zundert; Tom Oomen (Int. J. Control, 2019)

Mitigation of Torsional Vibrations in Drilling Systems: A Robust Control Approach. - Thijs Vromen; Cam-Hing Dai; Nathan van de Wouw; Tom Oomen; Patricia Astrid; Apostolos Doris; Henk Nijmeijer (IEEE Trans. Control. Syst. Technol., 2019)

On Frequency Response Function Identification for Advanced Motion Control. - Enzo Evers; Robbert Voorhoeve; Tom Oomen (AMC, 2020)

Suppressing Position-Dependent Disturbances in Repetitive Control: With Application to a Substrate Carrier System. - Noud Mooren; Gert Witvoet; Ibrahim Açan; Joep Kooijman; Tom Oomen (AMC, 2020)

Learning for Advanced Motion Control. - Tom Oomen (AMC, 2020)

Hybrid-MEM-Element Feedforward: With Application to Hysteretic Piezoelectric Actuators. - Nard Strijbosch; Tom Oomen (CDC, 2020)

Kernel-based identification of non-causal systems with application to inverse model control. - Lennart Blanken; Tom Oomen (Autom., 2020)

Improving mechanical ventilation for patient care through repetitive control. - Joey Reinders; Ruben Verkade; Bram Hunnekens; Nathan van de Wouw; Tom Oomen (CoRR, 2020)

Temperature-Dependent Modeling of Thermoelectric Elements. - Enzo Evers; Rens Slenders; Rob W. van Gils; Tom Oomen (CoRR, 2020)

Commutation-Angle Iterative Learning Control for Intermittent Data: Enhancing Piezo-Stepper Actuator Waveforms. - Leontine Aarnoudse; Nard Strijbosch; Edwin Verschueren; Tom Oomen (CoRR, 2020)

Gaussian Process Repetitive Control for Suppressing Spatial Disturbances. - Noud Mooren; Gert Witvoet; Tom Oomen (CoRR, 2020)

On the Role of Models in Learning Control: Actor-Critic Iterative Learning Control. - Maurice Poot; Jim Portegies; Tom Oomen (CoRR, 2020)

Multivariable Iterative Learning Control Design Procedures: From Decentralized to Centralized, Illustrated on an Industrial Printer. - Lennart Blanken; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2020)

Iterative Identification and Control Using Non-normalized Coprime Factors With Application in Wafer Stage Motion Control. - Frank Boeren; Alexander Lanzon; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2020)

Beyond Performance/Cost Tradeoffs in Motion Control: A Multirate Feedforward Design With Application to a Dual-Stage Wafer System. - Jurgen van Zundert; Tom Oomen; Jan Verhaegh; Wouter H. T. M. Aangenent; Duarte J. Antunes; W. P. M. H. Heemels (IEEE Trans. Control. Syst. Technol., 2020)

Kernel-Based Learning Control for Iteration-Varying Tasks Applied to a Printer With Friction. - Maurice Poot; Jim Portegies; Tom Oomen (AIM, 2021)

Model-free Multi-variable Learning Control of a Five Axis Nanopositioning Stage. - Thijs Sieswerda; Andrew J. Fleming; Tom Oomen (AIM, 2021)

Systematic feedback control design for scattered light noise mitigation in Virgo's MultiSAS. - Mathyn van Dael; Gert Witvoet; Bas Swinkels; Tom Oomen (AMC, 2021)

Peak Amplitude-Constrained Experiment Design for FRF Identification of MIMO Motion Systems. - Nic Dirkx; Marcel Bosselaar; Tom Oomen (AMC, 2021)

Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder. - Max van Haren; Maurice Poot; Dragan Kostic; Robin van Es; Jim Portegies; Tom Oomen (AMC, 2021)

A Gaussian Process Approach to Multiple Internal Models in Repetitive Control. - Noud Mooren; Gert Witvoet; Tom Oomen (AMC, 2021)

Closed-loop Aspects in MIMO Fault Diagnosis with Application to Precision Mechatronics. - Koen Classens; W. P. M. H. Heemels; Tom Oomen (ACC, 2021)

Suppressing non-collocated disturbances in inferential motion control: with application to a wafer stage. - Nic Dirkx; Noud Mooren; Tom Oomen (ACC, 2021)

Accurate H∞iH∞-Norm Estimation via Finite-Frequency Norms of Local Parametric Models. - Paul Tacx; Tom Oomen (ACC, 2021)

Glitch Compensation for a Digital-to-Analogue Converter. - Stan Verbeek; Tom Oomen; Arnfinn Aas Eielsen (ACC, 2021)

Linear repetitive control for a nonlinear mechanical ventilation system using feedback linearization. - Joey Reinders; Bram Hunnekens; Tom Oomen; Nathan van de Wouw (CCTA, 2021)

Conjugate Gradient MIMO Iterative Learning Control Using Data-Driven Stochastic Gradients. - Leontine Aarnoudse; Tom Oomen (CDC, 2021)

Intermittent Sampling in Repetitive Control: Exploiting Time-Varying Measurements. - Johan Kon; Nard Strijbosch; Sjirk H. Koekebakker; Tom Oomen (CDC, 2021)

Digital Twins in Mechatronics: From Model-based Control to Predictive Maintenance. - Koen Classens; W. P. Maurice H. Heemels; Tom Oomen (DTPI, 2021)

Control- Relevant Neural Networks for Intelligent Motion Feedforward. - Leontine Aarnoudse; Wataru Ohnishi; Maurice Poot; Paul Tacx; Nard Strijbosch; Tom Oomen (ICM, 2021)

A Closed-Loop Perspective on Fault Detection for Precision Motion Control: With Application to an Overactuated System. - Koen Classens; W. P. M. H. Heemels; Tom Oomen (ICM, 2021)

Suppressing spatially distributed disturbances by exploiting additional sensors and actuators in inferential motion control. - Nic Dirkx; Tom Oomen (ICM, 2021)

Multirate State Tracking for Improving Intersample Behavior in Iterative Learning Control. - Wataru Ohnishi; Nard Strijbosch; Tom Oomen (ICM, 2021)

Data-dependent orthogonal polynomials on generalized circles: A unified approach applied to δ-domain identification. - Robbert Voorhoeve; Tom Oomen (Autom., 2021)

Frequency-Domain Data-Driven Controller Synthesis for Unstable LPV Systems. - Tom Bloemers; Roland Tóth; Tom Oomen (CoRR, 2021)

Iterative learning control with discrete-time nonlinear nonminimum phase models via stable inversion. - Isaac A. Spiegel; Nard Strijbosch; Tom Oomen; Kira Barton (CoRR, 2021)

Learning nonlinear feedforward: a Gaussian Process Approach Applied to a Printer with Friction. - Max van Meer; Maurice Poot; Jim Portegies; Tom Oomen (CoRR, 2021)

Model-Free Learning for Massive MIMO Systems: Stochastic Approximation Adjoint Iterative Learning Control. - Leontine Aarnoudse; Tom Oomen (IEEE Control. Syst. Lett., 2021)

Adaptive Control for Mechanical Ventilation for Improved Pressure Support. - Joey Reinders; Bram Hunnekens; Frank Heck; Tom Oomen; Nathan van de Wouw (IEEE Trans. Control. Syst. Technol., 2021)

Identifying Position-Dependent Mechanical Systems: A Modal Approach Applied to a Flexible Wafer Stage. - Robbert Voorhoeve; Robin de Rozario; Wouter H. T. M. Aangenent; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2021)

Position-Dependent Snap Feedforward: A Gaussian Process Framework. - Max van Haren; Maurice Poot; Jim Portegies; Tom Oomen (ACC, 2022)

Physics-Guided Neural Networks for Feedforward Control: An Orthogonal Projection-Based Approach. - Johan Kon; Dennis Bruijnen; Jeroen van de Wijdeven; Marcel Heertjes; Tom Oomen (ACC, 2022)

Feedforward of Sampled-Data System for High-Precision Motion Control using Basis Functions with ZOH Differentiator. - Masahiro Mae; Max van Haren; Wataru Ohnishi; Tom Oomen; Hiroshi Fujimoto (ACC, 2022)

Gaussian Processes for Advanced Motion Control*. - Maurice Poot; Jim Portegies; Noud Mooren; Max van Haren; Max van Meer; Tom Oomen (ACC, 2022)

Bode Analysis of Uncertain Multivariable Systems. - Paul Tacx; Tom Oomen (ACC, 2022)

A non-causal approach for suppressing the estimation delay of state observer. - Kentaro Tsurumoto; Wataru Ohnishi; Takafumi Koseki; Nard Strijbosch; Tom Oomen (ACC, 2022)

Cross-Coupled Iterative Learning Control for Complex Systems: A Monotonically Convergent and Computationally Efficient Approach *. - Leontine Aarnoudse; Johan Kon; Koen Classens; Max van Meer; Maurice Poot; Paul Tacx; Nard Strijbosch; Tom Oomen (CDC, 2022)

Uncertain uncertainty in data-driven stochastic optimization: towards structured ambiguity sets. - Lotfi M. Chaouach; Dimitris Boskos; Tom Oomen (CDC, 2022)

Frequency Domain Identification of Multirate Systems: A Lifted Local Polynomial Modeling Approach. - Max van Haren; Lennart Blanken; Tom Oomen (CDC, 2022)

Unifying Model-Based and Neural Network Feedforward: Physics-Guided Neural Networks with Linear Autoregressive Dynamics. - Johan Kon; Dennis Bruijnen; Jeroen van de Wijdeven; Marcel Heertjes; Tom Oomen (CDC, 2022)

Data-enabled predictive control with instrumental variables: the direct equivalence with subspace predictive control. - Jan-Willem van Wingerden; Sebastiaan Paul Mulders; Rogier Dinkla; Tom Oomen; Michel Verhaegen (CDC, 2022)

Gaussian process repetitive control: Beyond periodic internal models through kernels. - Noud Mooren; Gert Witvoet; Tom Oomen (Autom., 2022)

Iterative learning control for intermittently sampled data: Monotonic convergence, design, and applications. - Nard Strijbosch; Tom Oomen (Autom., 2022)

Data-driven feedback linearisation using model predictive control. - Merijn Floren; Koen Classens; Tom Oomen; Jean-Philippe Noël (CoRR, 2022)

Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution. - Johan Kon; Marcel Heertjes; Tom Oomen (CoRR, 2022)

Automated MIMO Motion Feedforward Control: Efficient Learning through Data-Driven Gradients via Adjoint Experiments and Stochastic Approximation. - Leontine Aarnoudse; Tom Oomen (CoRR, 2022)

Cross-Coupled Iterative Learning Control for Complex Systems: A Monotonically Convergent and Computationally Efficient Approach. - Leontine Aarnoudse; Johan Kon; Koen Classens; Max van Meer; Maurice Poot; Paul Tacx; Nard Strijbosch; Tom Oomen (CoRR, 2022)

Optimal Commutation for Switched Reluctance Motors using Gaussian Process Regression. - Max van Meer; Gert Witvoet; Tom Oomen (CoRR, 2022)

Feedforward Control in the Presence of Input Nonlinearities: A Learning-based Approach. - Jilles van Hulst; Maurice Poot; Dragan Kostic; Kai Wa Yan; Jim Portegies; Tom Oomen (CoRR, 2022)

Basis Function feedforward for Position-Dependent Systems. - Max van Haren; Lennart Blanken; Tom Oomen (CoRR, 2022)

Frequency Response Data-Driven LPV Controller Synthesis for MIMO Systems. - Tom Bloemers; Tom Oomen; Roland Tóth (IEEE Control. Syst. Lett., 2022)

A Fast Smoothing-Based Algorithm to Generate l∞-Norm Constrained Signals for Multivariable Experiment Design. - Nic Dirkx; Marcel Bosselaar; Tom Oomen (IEEE Control. Syst. Lett., 2022)

Hysteresis Feedforward Compensation: A Direct Tuning Approach Using Hybrid-MEM-Elements. - Nard Strijbosch; Koen Tiels; Tom Oomen (IEEE Control. Syst. Lett., 2022)

Direct data-driven design of LPV controllers with soft performance specifications. - Max van Meer; Valentina Breschi; Tom Oomen; Simone Formentin (J. Frankl. Inst., 2022)

Frequency Response Data-Based LPV Controller Synthesis Applied to a Control Moment Gyroscope. - Tom Bloemers; Tom Oomen; Roland Tóth (IEEE Trans. Control. Syst. Technol., 2022)

Incorporating Prior Knowledge in Local Parametric Modeling for Frequency Response Measurements: Applied to Thermal/Mechanical Systems. - Enzo Evers; Bram de Jager; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2022)

Data-Driven LIDAR Feedforward Predictive Wind Turbine Control. - Rogier Dinkla; Tom Oomen; Jan-Willem van Wingerden; Sebastiaan Paul Mulders (CCTA, 2023)

Iterative Robust Experiment Design for MIMO System Identification via the S-Lemma. - Nic Dirkx; Koen Tiels; Tom Oomen (CCTA, 2023)

Novel Disturbance Observer Relevant Parametric System Identification Based on Robust Stability Criterion. - Hanul Jung; Paul Tacx; Tom Oomen; Sehoon Oh (CCTA, 2023)

Learning Control Applied to a Digital-to-analogue Converter. - Noa van Rijt; Ahmad Faza; Tom Oomen; Arnfinn Aas Eielsen (CCTA, 2023)

Efficient MIMO Iterative Feedback Tuning via Randomization. - Leontine Aarnoudse; Tom Oomen (CDC, 2023)

Nonlinear Repetitive Control for Mitigating Noise Amplification. - Leontine Aarnoudse; Alexey Pavlov 001; Johan Kon; Tom Oomen (CDC, 2023)

Comparing Structured Ambiguity Sets for Stochastic Optimization: Application to Uncertainty Quantification. - Lotfi M. Chaouach; Tom Oomen; Dimitris Boskos (CDC, 2023)

Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach. - Johan Kon; Jeroen van de Wijdeven; Dennis Bruijnen; Roland Tóth; Marcel Heertjes; Tom Oomen (CDC, 2023)

Nonlinear Bayesian Identification for Motor Commutation: Applied to Switched Reluctance Motors. - Max van Meer; Rodrigo A. González; Gert Witvoet; Tom Oomen (CDC, 2023)

Rational Basis Functions in Iterative Learning Control for Multivariable Systems. - Maurice Poot; Jim Portegies; Dragan Kostic; Tom Oomen (CDC, 2023)

Robotic Control for Vibration Reduction of Swinging Products. - Robbert van der Kruk; Arend Jan van Noorden; Tom Oomen; René van de Molengraft; Herman Bruyninckx (ICM, 2023)

A Kernel-Based Identification Approach to LPV Feedforward: With Application to Motion Systems. - Max van Haren; Lennart Blanken; Tom Oomen (CoRR, 2023)

Learning for Precision Motion of an Interventional X-ray System: Add-on Physics-Guided Neural Network Feedforward Control. - Johan Kon; Naomi de Vos; Dennis Bruijnen; Jeroen van de Wijdeven; Marcel Heertjes; Tom Oomen (CoRR, 2023)

Cascaded Calibration of Mechatronic Systems via Bayesian Inference. - Max van Meer; Emre Deniz; Gert Witvoet; Tom Oomen (CoRR, 2023)

Identifying Lebesgue-sampled Continuous-time Impulse Response Models: A Kernel-based Approach. - Rodrigo A. González; Koen Tiels; Tom Oomen (CoRR, 2023)

Direct Shaping of Minimum and Maximum Singular Values: An ℋ/ℋ∞ Synthesis Approach for Fault Detection Filters. - Koen Classens; W. P. M. H. Heemels; Tom Oomen (CoRR, 2023)

Beyond Nyquist in Frequency Response Function Identification: Applied to Slow-Sampled Systems. - Max van Haren; Leonid Mirkin; Lennart Blanken; Tom Oomen (IEEE Control. Syst. Lett., 2023)

Gaussian Process Repetitive Control With Application to an Industrial Substrate Carrier System With Spatial Disturbances. - Noud Mooren; Gert Witvoet; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2023)

A Wavelet-Based Approach to FRF Identification From Incomplete Data. - Nic Dirkx; Koen Tiels; Tom Oomen (IEEE Trans. Instrum. Meas., 2023)

Optimal iterative learning control design for continuous-time systems with nonidentical trial lengths using alternating projections between multiple sets. - Zhihe Zhuang; Hongfeng Tao; Yiyang Chen; Tom Oomen; Wojciech Paszke; Eric Rogers (J. Frankl. Inst., 2023)

Frequency Response Function-Based Learning Control: Analysis and Design for Finite-Time Convergence. - Robin de Rozario; Tom Oomen (IEEE Trans. Autom. Control., 2023)

Triggered Repetitive Control: Application to Mechanically Ventilated Patients. - Joey Reinders; David Elshove; Bram Hunnekens; Nathan van de Wouw; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2023)

Repetitive Control for Lur'e-Type Systems: Application to Mechanical Ventilation. - Joey Reinders; Mattia Giaccagli; Bram Hunnekens; Daniele Astolfi; Tom Oomen; Nathan van de Wouw (IEEE Trans. Control. Syst. Technol., 2023)

Memory-Element-Based Hysteresis: Identification and Compensation of a Piezoelectric Actuator. - Nard Strijbosch; Koen Tiels; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2023)

Automated Model-Free Commutation for Coarse Pointing Actuators in Free-Space Optical Communication. - Max van Meer; Kjell van Schie; Gert Witvoet; Tom Oomen (AIM, 2024)

Optimal Fault Detection for Closed-Loop Linear Uncertain Systems. - Koen Classens; Tjeerd Ickenroth; Jeroen van de Wijdeven; W. P. Maurice H. Heemels; Tom Oomen (CDC, 2024)

Data-enabled Predictive Repetitive Control. - Rogier Dinkla; Tom Oomen; Sebastiaan Paul Mulders; Jan-Willem van Wingerden (CDC, 2024)

Iterative Learning Control - Algorithms, Applications and Future Research Directions. - Eric Rogers; Bing Chu; Kevin L. Moore 001; Tom Oomen; Ying Tan (CDC, 2024)

Iterative interaction decoupling for multivariate time-varying systems applied to a Gravitational Wave Detector. - Mathyn van Dael; Gert Witvoet; Bas Swinkels; Diego Bersanetti; Manuel Pinto; Julia Casanueva; Maddalena Mantovani; Piernicola Spinicelli; Camilla De Rossi; Tom Oomen (ECC, 2024)

Unconstrained Parameterization of Stable LPV Input-Output Models: with Application to System Identification. - Johan Kon; Jeroen van de Wijdeven; Dennis Bruijnen; Roland Tóth; Marcel Heertjes; Tom Oomen (ECC, 2024)

Robust Commutation Design: Applied to Switched Reluctance Motors. - Max van Meer; Gert Witvoet; Tom Oomen (ECC, 2024)

Combined Time-Domain Optimization Design for Task-Flexible and High Performance ILC. - Kentaro Tsurumoto; Wataru Ohnishi; Takafumi Koseki; Max van Haren; Tom Oomen (ECC, 2024)

Kernel-based identification using Lebesgue-sampled data. - Rodrigo A. González; Koen Tiels; Tom Oomen (Autom., 2024)

Reset-free data-driven gain estimation: Power iteration using reversed-circulant matrices. - Tom Oomen; Cristian R. Rojas (Autom., 2024)

Closed-loop Data-Enabled Predictive Control and its equivalence with Closed-loop Subspace Predictive Control. - Rogier Dinkla; Sebastiaan Paul Mulders; Tom Oomen; Jan-Willem van Wingerden (CoRR, 2024)

Statistical Analysis of Block Coordinate Descent Algorithms for Linear Continuous-Time System Identification. - Rodrigo A. González; Koen Classens; Cristian R. Rojas; James S. Welsh; Tom Oomen (IEEE Control. Syst. Lett., 2024)

Sampling in Parametric and Nonparametric System Identification: Aliasing, Input Conditions, and Consistency. - Rodrigo A. González; Max van Haren; Tom Oomen; Cristian R. Rojas (IEEE Control. Syst. Lett., 2024)

Guaranteeing Stability in Structured Input-Output Models: With Application to System Identification. - Johan Kon; Roland Tóth; Jeroen van de Wijdeven; Marcel Heertjes; Tom Oomen (IEEE Control. Syst. Lett., 2024)

Scaled graphs for reset control system analysis. - Sebastiaan van den Eijnden; Thomas Chaffey 001; Tom Oomen; W. P. M. H. Heemels (Eur. J. Control, 2024)

A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC. - Max van Haren; Kentaro Tsurumoto; Masahiro Mae; Lennart Blanken; Wataru Ohnishi; Tom Oomen (Eur. J. Control, 2024)

Control-relevant neural networks for feedforward control with preview: Applied to an industrial flatbed printer. - Leontine Aarnoudse; Johan Kon; Wataru Ohnishi; Maurice Poot; Paul Tacx; Nard Strijbosch; Tom Oomen (IFAC J. Syst. Control., 2024)

Improving breathing effort estimation in mechanical ventilation via optimal experiment design. - Lars Van De Kamp; Bram Hunnekens; Nathan van de Wouw; Tom Oomen (IFAC J. Syst. Control., 2024)

Automatic patient-ventilator asynchrony detection framework using objective asynchrony definitions. - Lars Van De Kamp; Joey Reinders; Bram Hunnekens; Tom Oomen; Nathan van de Wouw (IFAC J. Syst. Control., 2024)

Closed-loop Data-enabled Predictive Control and its equivalence with Closed-loop Subspace Predictive Control: source code. - Rogier Dinkla; Sebastiaan Paul Mulders; Tom Oomen; Jan-Willem van Wingerden (Zenodo, 2024)

Closed-loop Data-enabled Predictive Control and its equivalence with Closed-loop Subspace Predictive Control: dataset. - Rogier Dinkla; Sebastiaan Paul Mulders; Tom Oomen; Jan-Willem van Wingerden (Zenodo, 2024)

Stable Inversion of Piecewise Affine Systems With Application to Feedforward and Iterative Learning Control. - Isaac A. Spiegel; Nard Strijbosch; Robin de Rozario; Tom Oomen; Kira Barton (IEEE Trans. Autom. Control., 2024)

Vibration Control Under Frequency-Varying Disturbances With Application to Satellites. - Tom Bloemers; Sjoerd Leemrijse; Valentin Preda; Fabrice Boquet; Tom Oomen; Roland Tóth (IEEE Trans. Control. Syst. Technol., 2024)

Position-Dependent Motion Feedforward via Gaussian Processes: Applied to Snap and Force Ripple in Semiconductor Equipment. - Maurice Poot; Max van Haren; Dragan Kostic; Jim Portegies; Tom Oomen (IEEE Trans. Control. Syst. Technol., 2024)

Automatic Basis Function Selection in Iterative Learning Control: A Sparsity-Promoting Approach Applied to an Industrial Printer. - Tjeerd Ickenroth; Max van Haren; Johan Kon; Max van Meer; Jilles van Hulst; Tom Oomen (ACC, 2025)

MIMO-decoupling to improve pressure and flow tracking in mechanical ventilation. - Lars Van De Kamp; Isabelle Franklin; Bas van Loon; Tom Oomen; Nathan van de Wouw (ACC, 2025)

Nonlinear iterative learning control for discriminating between disturbances. - Leontine Aarnoudse; Alexey Pavlov 001; Tom Oomen (Autom., 2025)

Identification of additive continuous-time systems in open and closed loop. - Rodrigo A. González; Koen Classens; Cristian R. Rojas; James S. Welsh; Tom Oomen (Autom., 2025)

Identification of Additive Multivariable Continuous-Time Systems. - M. van der Hulst; Rodrigo A. González; Koen Classens; Nic Dirkx; Jeroen van de Wijdeven; Tom Oomen (IEEE Control. Syst. Lett., 2025)

Direct Bayesian Identification of Inverse Linear Systems. - Rikuto Suzuki; Tom Oomen; Rodrigo A. González (IEEE Control. Syst. Lett., 2025)

Recursive identification of structured systems: An instrumental-variable approach applied to mechanical systems. - Koen Classens; Rodrigo A. González; Tom Oomen (Eur. J. Control, 2025)

A Direct State-Space Realization of Discrete-Time Linear Parameter-Varying Input-Output Models. - Johan Kon; Roland Tóth; Jeroen van de Wijdeven; Marcel Heertjes; Tom Oomen (CoRR, 2025)

Lifted Frequency-Domain Identification of Closed-Loop Multirate Systems: Applied to Dual-Stage Actuator Hard Disk Drives. - Max van Haren; Masahiro Mae; Lennart Blanken; Tom Oomen (CoRR, 2025)

System Identification Beyond the Nyquist Frequency: A Kernel-Regularized Approach. - Max van Haren; Roy S. Smith; Tom Oomen (CoRR, 2025)

Parameter-Varying Feedforward Control: A Kernel-Based Learning Approach. - Max van Haren; Lennart Blanken; Tom Oomen (CoRR, 2025)

Local Rational Modeling for Identification Beyond the Nyquist Frequency: Applied to a Prototype Wafer Stage. - Max van Haren; Lennart Blanken; Koen Classens; Tom Oomen (CoRR, 2025)

Frequency domain identification for multivariable motion control systems: Applied to a prototype wafer stage. - Maarten van der Hulst; Rodrigo A. González; Koen Classens; Paul Tacx; Nic Dirkx; Jeroen van de Wijdeven; Tom Oomen (CoRR, 2025)

Performance Analysis of Multirate Systems: A Direct Frequency-Domain Identification Approach. - Max van Haren; Lennart Blanken; Tom Oomen (CoRR, 2025)

Compensating Hysteresis and Mechanical Misalignment in Piezo-Stepper Actuators. - Max van Meer; Tim van Meijel; Emile van Halsema; Edwin Verschueren; Gert Witvoet; Tom Oomen (CoRR, 2025)

GraFIT: A toolbox for fast and accurate frequency response identification in Gravitational Wave Detectors. - Mathyn van Dael; Max van Haren; Gert Witvoet; Bas Swinkels; Tom Oomen (CoRR, 2025)

Exploiting Structure in MIMO Scaled Graph Analysis. - Timo de Groot; Tom Oomen; Sebastiaan van den Eijnden (CoRR, 2025)

Self-Calibrating Position Measurements: Applied to Imperfect Hall Sensors. - Max van Meer; Marijn van Noije; Koen Tiels; Enzo Evers; Lennart Blanken; Gert Witvoet; Tom Oomen (CoRR, 2025)

Statistically Optimal Structured Additive MIMO Continuous-time System Identification. - Rodrigo A. González; Maarten van der Hulst; Koen Classens; Tom Oomen (CoRR, 2025)

Truncated Gaussian Noise Estimation in State-Space Models. - Rodrigo A. González; Angel L. Cedeño; Koen Tiels; Tom Oomen (CoRR, 2025)

Experimentally-efficient data-driven rational feedforward control for multivariable systems. - Maurice Poot; Jim Portegies; Dragan Kostic; Tom Oomen (Int. J. Control, 2025)