DocumentCode :
728429
Title :
Iterative learning control for load control of smart turbine blades with variable rotation rates
Author :
Tutty, Owen ; Blackwell, Mark ; Rogers, Eric ; Sandberg, Richard
Author_Institution :
Fac. of Eng. & the Environ., Univ. of Southampton, Southampton, UK
fYear :
2015
fDate :
1-3 July 2015
Firstpage :
3690
Lastpage :
3695
Abstract :
Previous work has demonstrated the feasibility of iterative learning control applied to wind turbine blades with smart rotors in order to smooth the natural fluctuations in aerodynamic load through vorticity generation at the trailing edge using devices such as flaps. Here we extend this work by a) including a more physically realistic model of the flow by adding a model of the wake which evolves with the flow downstream of the blade, and b) allowing for fluctuations in the period of rotation of the blade, reflecting a situation found in practise. Again, ILC control is found to produce a significant reduction in 2-norm and ∞-norm measures of the variation of the load.
Keywords :
aerodynamics; blades; iterative learning control; rotors; wakes; wind turbines; ∞-norm measures; 2-norm measures; ILC; aerodynamic load; flaps; iterative learning control; smart rotors; smart turbine blade load control; variable rotation rates; vorticity generation; wake; wind turbine blades; Atmospheric modeling; Automotive components; Blades; Computational fluid dynamics; Load modeling; Mathematical model; Wind turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
Type :
conf
DOI :
10.1109/ACC.2015.7171903
Filename :
7171903
Link To Document :
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