6 papers · 1 filter
Automatic Basis Function Selection in Iterative Learning Control: A Sparsity-Promoting Approach Applied to an Industrial Printer
Tjeerd Ickenroth, Max van Haren, Johan Kon +3
Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past i…
Robust Commutation Design: Applied to Switched Reluctance Motors
Max van Meer, Gert Witvoet, Tom Oomen
Switched Reluctance Motors (SRMs) are cost-effective electric actuators that utilize magnetic reluctance to generate torque, with torque ripple arising from unaccounted manufacturi…
Nonlinear Bayesian Identification for Motor Commutation: Applied to Switched Reluctance Motors
Max van Meer, Rodrigo A. González, Gert Witvoet +1
Switched Reluctance Motors (SRMs) enable power-efficient actuation with mechanically simple designs. This paper aims to identify the nonlinear relationship between torque, rotor an…
Cascaded Calibration of Mechatronic Systems via Bayesian Inference
Max van Meer, Emre Deniz, Gert Witvoet +1
Sensors in high-precision mechatronic systems require accurate calibration, which is achieved using test beds that, in turn, require even more accurate calibration. The aim of this…
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…
Learning nonlinear feedforward: a Gaussian Process Approach Applied to a Printer with Friction
Max van Meer, Maurice Poot, Jim Portegies +1
Feedforward control is essential to achieving good tracking performance in positioning systems. The aim of this paper is to develop an identification strategy for inverse models of…