Data-driven repetitive control: Wind tunnel experiments under turbulent conditions. (November 2018)

• Record Type: Journal Article
• Authors: Frederik, Joeri; Kröger, Lars; Gülker, Gerd; van Wingerden, Jan-Willem
• Is Part Of: Control engineering practice. Volume 80(2018)
• Page Start: 105
• Page End: 115
• Publication Date: 2018-11
• Subjects: Data-driven control -- Individual pitch control -- Load alleviation -- Repetitive control -- Subspace identification -- Wind energy -- Active grid -- Wind tunnel experiments; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.08.011
• Languages: English
• ISSNs: 0967-0661

Abstract

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.