Papers
1 Huang, Y., & Zhao, X. (2025). Wind farm control via offline reinforcement learning with adversarial training. IEEE Transactions on Automation Science and Engineering. DOI: 10.1109/TASE.2025.3548565
2 Heidari, J., Kayedpour, N., Vandevelde, L., & Crevecoeur, G. (2025). Estimating Tower Vibrations with Data-Driven Models: Possibility of Optimizing Control Actions to Reduce Loads on Wind Turbine. Presented at Wind Energy Science Conference (WESC) 2025.
3 Heidari, J., Kayedpour, N., Vandevelde, L., & Crevecoeur, G. SCADA-Compatible Sliding Window Multi-Input Multi-Output Data-Driven Modelling for Wind Turbines: A Validation Case
4 Knudsen, T., Hassani, S., & Wisniewski, R. (2025). Stochastic MPC with Focus on Probabilistic Constraints with Application to Wind Turbine Control. Proceeding of the 2025 American Control Conference (ACC).
5 Zhang, J., & Zhao, X. (2024). Reconstruction of dynamic wind turbine wake flow fields from virtual Lidar measurements via physics-informed neural networks. Journal of Physics: Conference Series, 2767.
https://iopscience.iop.org/article/10.1088/1742-6596/2767/9/092017
6 Heidari, J., Kayedpour, N., Vandevelde, L., & Crevecoeur, G. (2024). Physics-Based, Data-Augmented Model for Wind Turbine Control Design. Journal of Physics: Conference Series, 3025(1), 012008. DOI: 10.1088/1742-6596/3025/1/012008
