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Iterative learning control for load control of smart turbine blades with variable rotation rates | IEEE Conference Publication | IEEE Xplore

Iterative learning control for load control of smart turbine blades with variable rotation rates


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 ...Show More

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.
Date of Conference: 01-03 July 2015
Date Added to IEEE Xplore: 30 July 2015
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Conference Location: Chicago, IL, USA

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