L2-gain analysis of periodic event-triggered systems with varying delays using lifting techniques. - N. W. A. Strijbosch; Geir E. Dullerud; Andrew R. Teel; W. P. Maurice H. Heemels (CDC, 2017)

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

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

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

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

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

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

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

$ mathcal {L}_2$-Gain Analysis of Periodic Event-Triggered Control and Self-Triggered Control Using Lifting. - Nard Strijbosch; Geir E. Dullerud; Andrew R. Teel; W. P. M. H. Heemels (IEEE Trans. Autom. Control., 2021)

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)

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

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

Physics-guided neural networks for feedforward control with input-to-state stability guarantees. - Max Bolderman; Hans Butler; Sjirk H. Koekebakker; Eelco van Horssen; Ramidin Kamidi; Theresa Spaan-Burke; Nard Strijbosch; Mircea Lazar (CoRR, 2023)

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

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)

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)