activity
20202024
most citedPhysics-guided neural networks for feedforward control with input-to-state stability guarantees

34 citations · 58 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2024★ 6 cited

Stable Inversion of Piecewise Affine Systems with Application to Feedforward and Iterative Learning Control

Isaac A. Spiegel, Nard Strijbosch, Robin de Rozario +2

Model inversion is a fundamental technique in feedforward control. Unstable inverse models present a challenge in that useful feedforward control trajectories cannot be generated b…

eess.SY2023★ 34 cited

Physics-guided neural networks for feedforward control with input-to-state stability guarantees

Max Bolderman, Hans Butler, Sjirk Koekebakker +5

The increasing demand on precision and throughput within high-precision mechatronics industries requires a new generation of feedforward controllers with higher accuracy than exist…

eess.SY2022

Cross-Coupled Iterative Learning Control for Complex Systems: A Monotonically Convergent and Computationally Efficient Approach

Leontine Aarnoudse, Johan Kon, Koen Classens +5

Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. Th…

eess.SY2021★ 2 cited

Intermittent Sampling in Repetitive Control: Exploiting Time-Varying Measurements

Johan Kon, Nard Strijbosch, Sjirk Koekebakker +1

The performance increase up to the sensor resolution in repetitive control (RC) invalidates the standard assumption in RC that data is available at equidistant time instances, e.g.…

eess.SY2021★ 11 cited

Iterative learning control with discrete-time nonlinear nonminimum phase models via stable inversion

Isaac A Spiegel, Nard Strijbosch, Tom Oomen +1

Output reference tracking can be improved by iteratively learning from past data to inform the design of feedforward control inputs for subsequent tracking attempts. This process i…

eess.SY2020★ 5 cited

Commutation-Angle Iterative Learning Control for Intermittent Data: Enhancing Piezo-Stepper Actuator Waveforms

Leontine Aarnoudse, Nard Strijbosch, Edwin Verschueren +1

Piezo-stepper actuators are used in many nanopositioning systems due to their high resolution, high stiffness, fast response, and the ability to position a mover over an infinite s…