M Maarten Steinbuch

TL;DR: In this paper, a technique is presented to design input signals for point-to-point control problems with the property of minimal excitation of parasitic system oscillations, compared to impulse based input design techniques in experiments performed on an industrial XY-positioning table.

TL;DR: In this paper, a new control algorithm based on a combination of dynamic programming and classical optimal control theory is proposed for the Energy Management System in parallel HEVs to improve the fuel economy over a preview route segment.

TL;DR: In this article, a feedback control approach for real-time, autonomous suppression and stabilization of tearing modes in a tokamak is presented. But the system combines an electron cyclotron emission diagnostic for sensing of the tearing mode in the same sight line with a steerable ECRH/ECCD antenna, and set-points are generated in real time and forwarded to the steerable launcher and as a modulation pulse train to the gyrotron.

TL;DR: Repetitive and iterative learning control are control strategies for systems that perform repetitive tasks or on which periodic disturbances act if disturbances are position dependent or if dynamics are excited during each point to point motion.

TL;DR: This work shows how social forces based motion models can exploit typical motion patterns summarized by growing hidden Markov models (GHMMs) that can be learned from data online and without human intervention.