Articles | Volume 5, issue 4
Wind Energ. Sci., 5, 1579–1600, 2020
https://doi.org/10.5194/wes-5-1579-2020
Wind Energ. Sci., 5, 1579–1600, 2020
https://doi.org/10.5194/wes-5-1579-2020
Research article
17 Nov 2020
Research article | 17 Nov 2020

Automatic controller tuning using a zeroth-order optimization algorithm

Daniel S. Zalkind et al.

Related authors

System-level design studies for large rotors
Daniel S. Zalkind, Gavin K. Ananda, Mayank Chetan, Dana P. Martin, Christopher J. Bay, Kathryn E. Johnson, Eric Loth, D. Todd Griffith, Michael S. Selig, and Lucy Y. Pao
Wind Energ. Sci., 4, 595–618, https://doi.org/10.5194/wes-4-595-2019,https://doi.org/10.5194/wes-4-595-2019, 2019
Short summary
Optimal Output Feedback H Torque Control of a Wind Turbine Rotor using a Parametrically Scheduled Model
Dana Martin, Kathryn Johnson, Christopher Bay, Daniel Zalkind, Lucy Pao, Meghan Kaminski, and Eric Loth
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-27,https://doi.org/10.5194/wes-2018-27, 2018
Revised manuscript not accepted
Short summary

Related subject area

Control and system identification
Load reduction for wind turbines: an output-constrained, subspace predictive repetitive control approach
Yichao Liu, Riccardo Ferrari, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 523–537, https://doi.org/10.5194/wes-7-523-2022,https://doi.org/10.5194/wes-7-523-2022, 2022
Short summary
A reference open-source controller for fixed and floating offshore wind turbines
Nikhar J. Abbas, Daniel S. Zalkind, Lucy Pao, and Alan Wright
Wind Energ. Sci., 7, 53–73, https://doi.org/10.5194/wes-7-53-2022,https://doi.org/10.5194/wes-7-53-2022, 2022
Short summary
Experimental results of wake steering using fixed angles
Paul Fleming, Michael Sinner, Tom Young, Marine Lannic, Jennifer King, Eric Simley, and Bart Doekemeijer
Wind Energ. Sci., 6, 1521–1531, https://doi.org/10.5194/wes-6-1521-2021,https://doi.org/10.5194/wes-6-1521-2021, 2021
Short summary
Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance
Eric Simley, Paul Fleming, Nicolas Girard, Lucas Alloin, Emma Godefroy, and Thomas Duc
Wind Energ. Sci., 6, 1427–1453, https://doi.org/10.5194/wes-6-1427-2021,https://doi.org/10.5194/wes-6-1427-2021, 2021
Short summary
Model-based design of a wave-feedforward control strategy in floating wind turbines
Alessandro Fontanella, Mees Al, Jan-Willem van Wingerden, and Marco Belloli
Wind Energ. Sci., 6, 885–901, https://doi.org/10.5194/wes-6-885-2021,https://doi.org/10.5194/wes-6-885-2021, 2021
Short summary

Cited articles

Bertsekas, D.: Nonlinear Programming, Athena Scientific, Belmont, Mass., 1999. a
Booker, A. J., Dennis, J. E., Frank, P. D., Serafini, D. B., Torczon, V., and Trosset, M. W.: A rigorous framework for optimization of expensive functions by surrogates, Struct. Optimization, 17, 1–13, https://doi.org/10.1007/BF01197708, 1999. a
Bottasso, C. L., Campagnolo, F., and Croce, A.: Multi-disciplinary constrained optimization of wind turbines, Multibody Syst. Dyn., 27, 21–53, https://doi.org/10.1007/s11044-011-9271-x, 2012. a
Box, G. E. P. and Wilson, K. B.: On the experimental attainment of optimum conditions, J. Roy. Stat. Soc. B Met., 13, 1–45, 1951. a
Boyd, S. and Vandenberghe, L.: Convex Optimization, Cambridge University Press, New York, NY, USA, 2004. a
Download
Short summary
New wind turbine designs require updated control parameters, which should be optimal in terms of the performance measures that drive hardware design. We show how a zeroth-order optimization algorithm can randomly generate control parameters, use simulation results to estimate the gradient of the parameter space, and find an optimal set of those parameters. We then apply this automatic controller tuning procedure to three problems in wind turbine control.