| A tutorial on control-oriented modeling and control of wind farms S Boersma, BM Doekemeijer, PMO Gebraad, PA Fleming, J Annoni, ... 2017 American control conference (ACC), 1-18, 2017 | 244 | 2017 |
| A control-oriented dynamic wind farm model: WFSim S Boersma, B Doekemeijer, M Vali, J Meyers, JW van Wingerden Wind Energy Science 3 (1), 75-95, 2018 | 140 | 2018 |
| A constrained wind farm controller providing secondary frequency regulation: An LES study S Boersma, BM Doekemeijer, S Siniscalchi-Minna, JW Van Wingerden Renewable energy 134, 639-652, 2019 | 71 | 2019 |
| Adjoint-based model predictive control for optimal energy extraction in waked wind farms M Vali, V Petrović, S Boersma, JW van Wingerden, LY Pao, M Kühn Control Engineering Practice 84, 48-62, 2019 | 69 | 2019 |
| A control-oriented dynamic wind farm flow model:“WFSim” S Boersma, PMO Gebraad, M Vali, BM Doekemeijer, JW Van Wingerden Journal of Physics: Conference Series 753 (3), 032005, 2016 | 51 | 2016 |
| Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control BM Doekemeijer, S Boersma, LY Pao, T Knudsen, JW van Wingerden Wind Energy Science 3 (2), 749-765, 2018 | 44 | 2018 |
| Ensemble Kalman filtering for wind field estimation in wind farms BM Doekemeijer, S Boersma, LY Pao, JW van Wingerden 2017 American Control Conference (ACC), 19-24, 2017 | 41 | 2017 |
| Adjoint-based model predictive control of wind farms: Beyond the quasi steady-state power maximization M Vali, V Petrović, S Boersma, JW van Wingerden, M Kühn IFAC-PapersOnLine 50 (1), 4510-4515, 2017 | 29 | 2017 |
| Quasi linear parameter varying modeling for wind farm control using the 2D Navier-Stokes equations S Boersma, M Vali, M Kühn, JW van Wingerden 2016 American Control Conference (ACC), 4409-4414, 2016 | 29 | 2016 |
| A predictive control framework for optimal energy extraction of wind farms M Vali, JW van Wingerden, S Boersma, V Petrović, M Kühn Journal of Physics: Conference Series 753 (5), 052013, 2016 | 27 | 2016 |
| Enhanced Kalman filtering for a 2D CFD NS wind farm flow model BM Doekemeijer, JW Van Wingerden, S Boersma, LY Pao Journal of Physics: Conference Series 753 (5), 052015, 2016 | 26 | 2016 |
| Model predictive active power control of waked wind farms M Vali, V Petrović, S Boersma, JW van Wingerden, LY Pao, M Kühn 2018 Annual American Control Conference (ACC), 707-714, 2018 | 22 | 2018 |
| ℋ∞controller design for closed-loop wake redirection S Raach, JW van Wingerden, S Boersma, D Schlipf, PW Cheng 2017 American Control Conference (ACC), 703-708, 2017 | 17 | 2017 |
| Digital twins in the green life sciences WJ Knibbe, L Afman, S Boersma, MJ Bogaardt, J Evers, F Van Evert, ... NJAS: Impact in Agricultural and Life Sciences 94 (1), 249-279, 2022 | 16 | 2022 |
| Stochastic model predictive control: uncertainty impact on wind farm power tracking S Boersma, BM Doekemeijer, T Keviczky, JW van Wingerdenl 2019 American Control Conference (ACC), 4167-4172, 2019 | 16 | 2019 |
| Dynamic flow model for real-time application in wind farm control A Rott, S Boersma, JW van Wingerden, M Kühn Journal of Physics: Conference Series 854 (1), 012039, 2017 | 16 | 2017 |
| Reinforcement Learning versus Model Predictive Control on greenhouse climate control B Morcego, W Yin, S Boersma, E Van Henten, V Puig, C Sun Computers and Electronics in Agriculture 215, 108372, 2023 | 15 | 2023 |
| Robust lidar-based closed-loop wake redirection for wind farm control S Raach, S Boersma, JW van Wingerden, D Schlipf, PW Cheng IFAC-PapersOnLine 50 (1), 4498-4503, 2017 | 15 | 2017 |
| Feedback-feedforward individual pitch control design for wind turbines with uncertain measurements R Ungurán, V Petrović, S Boersma, JW van Wingerden, LY Pao, M Kühn 2019 American Control Conference (ACC), 4151-4158, 2019 | 14 | 2019 |
| Chance-constrained stochastic MPC of greenhouse production systems with parametric uncertainty JL Svensen, X Cheng, S Boersma, C Sun Computers and Electronics in Agriculture 217, 108578, 2024 | 10 | 2024 |
