List of project related publications and references

Ritsma, F.R., Report on the Application of Machine Learning for Wind Turbine Control, TUD report, 2019

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

Ritsma, F.R., Approximate Dynamic Programming for Optimal Wind Turbine Control, to be submitted, 2020

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

Mulders, S.P., Wind turbine control: advances for load mitigations and hydraulic drivetrains , Ph.D. thesis, Delft, 2020

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

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

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

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

 

 

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