Fixed-structure sampled-data feedforward control for multivariable motion systems
Masahiro Mae (University of Tokyo)
Max Van Haren (Eindhoven University of Technology)
Koen Classens (Eindhoven University of Technology)
Wataru Ohnishi (University of Tokyo)
T.A.E. Oomen (TU Delft - Team Jan-Willem van Wingerden, Eindhoven University of Technology)
Hiroshi Fujimoto (University of Tokyo)
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Abstract
Increasing performance requirements in high-precision mechatronic systems lead to a situation where both multivariable and sampled-data implementation aspects need to be addressed. The aim of this paper is to develop a design framework for a multi-input multi-output feedforward controller to improve continuous-time tracking performance through learning. The sampled-data feedforward controller is designed with physically interpretable tuning parameters using a multirate zero-order-hold differentiator. The developed approach enables interaction compensation for multi-input multi-output systems and the feedforward controller parameters are updated through learning. The performance improvement is experimentally validated in a multi-input multi-output motion system compared to the conventional feedforward controllers.
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