List of project related publications and references
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Ritsma, F.R., Report on the Application of Machine Learning for Wind Turbine Control, TUD report, 2019 |
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Moustakis, N. Mulders, S.P. Kober, J. and van Wingerden, J.W., A Practical Bayesian Optimization Approach for the Optimal Estimation of the Rotor Effective Wind Speed, American Control Conference , 2019 |
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Ritsma, F.R., Approximate Dynamic Programming for Optimal Wind Turbine Control, to be submitted, 2020 |
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Mulders, S.P., A.K. Pamososuryo, and J.W. van Wingerden, Efficient tuning of Individual Pitch Control: A Bayesian Optimization Machine Learning approach, The science of making torque from wind , Delft, 2020 |
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Mulders, S.P., Wind turbine control: advances for load mitigations and hydraulic drivetrains , Ph.D. thesis, Delft, 2020 |
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Engels, W.P., Van der Hoek, D., Yu, W., Reyes Baez, R., Scheduled state feedback control of a wind turbine, The science of making torque from wind , Delft, 2020 |
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Yu, W., Engels, W.P., Stock-Williams, C.F.W., A Comparison of Multi-Objective Optimisation of Two Wind Turbine Controller Designs, The science of making torque from wind, Delft, 2020 |
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Stock-Williams, C.F.W., Yu, W., and Engels W.P., Multi-objective Bayesian Optimisation of Wind Turbine Controller Parameters, presented at MOPGP 2019 conference, Marrakech, Morocco, 2019 |
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Stock-Williams, C.F.W, Chugh, T., Rahat, A., Yu, W., What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?, Submitted to OR Spectrum , 2020 |