Frank Boeren

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Feedforward control can significantly improve the performance of a system through compensation of disturbances. By exploiting measured data from previous tasks and a suitable feedforward parametrization, iterative feedforward control simultaneously attains high performance and good extrapolability of tasks. This paper aims to show that earlier contributions(More)
The quality of model-based controllers hinges on a careful specification of performance and robustness requirements. In typical norm-based control designs, these performance and robustness requirements are specified in a scalar optimization criterion, even for complex multivariable systems. This paper aims to develop a novel and systematic approach for the(More)
Feedforward control can significantly improve the performance of industrial motion systems through compensation of the servo error induced by the reference signal. Recently, new feedforward tuning algorithms have been proposed that exploit measured data from previous tasks and a suitable feedforward parametrization to attain high servo performance. The aim(More)
Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework(More)
Next-generation high-precision positioning systems are designed to be lightweight, in order to enable an increase of the speed of movement. Lightweight systems tend to have complex dynamical system behavior at frequencies relevant for control. This flexible dynamical behavior should be explicitly addressed during controller design to i) improve robustness(More)
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