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Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification
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DOI：10.1016/j.conengprac.2014.12.015.png)
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Abstract
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Feedforward control can significantly enhance the performance of motion systems through compensation of known disturbances. This paper aims to develop a new procedure to tune a feedforward controller based on measured data obtained in finite time tasks. Hereto, a suitable feedforward parametrization is introduced that provides good extrapolation properties for a class of reference signals. Next, connections with closed-loop system identification are established. In particular, instrumental variables, which have been proven very useful in closed-loop system identification, are selected to tune the feedforward controller. These instrumental variables closely resemble traditional engineering tuning practice. In contrast to pre-existing approaches, the feedforward controller can be updated after each task, irrespective of noise acting on the system. Experimental results confirm the practical relevance of the proposed method. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Feedforward Control
Iterative learning control
Data-driven control
Precision motion systems
System identification
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