Data-driven repetitive control

Wind tunnel experiments under turbulent conditions

Journal article (2018)

Authors

J.A. Frederik Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
Lars Kröger University of Oldenburg
Gerd Gülker University of Oldenburg
J.W. van Wingerden Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
Research Group
Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2018 J.A. Frederik, Lars Kröger, Gerd Gülker, J.W. van Wingerden
DOI
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https://doi.org/10.1016/j.conengprac.2018.08.011
Wind energy Load alleviation Subspace identification Data-driven control Individual pitch control Active grid Repetitive control Wind tunnel experiments
More Info
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Published Date

2018

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

Abstract

A commonly applied method to reduce the cost of wind energy, is alleviating the periodic loads on turbine blades using Individual Pitch Control (IPC). In this paper, a data-driven IPC methodology called Subspace Predictive Repetitive Control (SPRC) is employed. The effectiveness of SPRC will be demonstrated on a scaled 2-bladed wind turbine. An open-jet wind tunnel with an innovative active grid is employed to generate reproducible turbulent wind conditions. A significant load reduction with limited actuator duty is achieved even under these high turbulent conditions. Furthermore, it will be demonstrated that SPRC is able to adapt to changing operating conditions.