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Contribution to Peer-Reviewed Journal (since 2015)
  • Routray, A., Hur, S. (2022). Full Operational Envelope Control of a Wind Turbine Using Model Predictive Control. IEEE Access, volume 10, 121940-121956.

  • Balakrishnan, R. K, Hur, S. (2022). Maximization of the Power Production of an Offshore Wind Farm. Applied Sciences, volume 12(8), 4013.

  • Routray, A., Hur, S. (2022). Leakage Current Mitigation of Photovoltaic System Using Optimized Predictive Control for Improved Efficiency. Applied Sciences, volume 12(2), 643.

  • Hur, S. (2021). Short-term wind speed prediction using Extended Kalman filter and machine learning. Energy Reports, volume 7, 1046-1054.

  • Reddy, Y., Hur, S. (2021). Comparison of Optimal Control Designs for a 5 MW Wind Turbine. Applied Sciences, volume 11(18), 8774.

  • Hur, S., Reddy, Y. (2021). Neural Network-Based Cost-Effective Estimation of Useful Variables to Improve Wind Turbine Control. Applied Sciences, volume 11(12), 5661.

  • Reddy, Y., Hwang, J. and Hur, S. (2021). Evaluation of Optimal Control Designs for a 5 MW Wind Turbine. Journal of Wind Energy, volume 12, issue 1, 36-44.

  • Hur, S. (2021). Reliable and cost-effective wind farm control strategy for offshore wind turbines. Renewable Energy, volume 163, 1265-1276.

  • Hur, S. (2019). Nonlinear Estimation of Important Variables using Neural Network in Wind Farms. Journal of Physics: Conference Series, volume 1222, 012022.

  • Hur, S. (2019). Estimation of Useful Variables in Wind Turbines and Farms Using Neural Networks and Extended Kalman Filter. IEEE Access, volume 7, 24017-24028.

  • Hur, S. (2018). Modelling and control of a wind turbine and farm. Energy, volume 156, 360-370.

  • Hur, S. and Leithead, W. (2018). Control Oriented Modelling of a Wind Turbine and Farm. Journal of Physics: Conference Series, volume 1037, 062020.

  • Hur, S. (2018). Real-time Adaptive Obstacle Avoidance Algorithm for Small Robots. IEMEK J. Embed. Sys. Appl. 13(2) 53-63.

  • Hur, S., Recalde-Camacho, L. and Leithead, W. (2017). Detection and compensation of anomalous conditions in a wind turbine. Energy, volume 124, 74-86.

  • Hur, S. and Leithead, W. (2017). Model Predictive and Linear Quadratic Gaussian Control of a Wind Turbine. Optimal Control Applications and Methods, volume 38, issue 1, 88-111.

  • Hur, S. and Leithead, W. (2016). Collective control strategy for a cluster of stall-regulated offshore wind turbines. Renewable Energy, volume 85, 1260-1270.

  • Hur, S. and Leithead, W. (2016). Adjustment of wind farm power output through flexible turbine operation using wind farm control. Wind Energy, volume 19, issue 9, 1667-1686.

  • Recalde-Camacho, L., Hur, S., and Leithead, W. (2016). Gusts detection in a horizontal wind turbine by monitoring of innovations error of an extended Kalman filter. Journal of Physics: Conference Series, volume 753, 052010.

  • Lei, T., Barnes, M., Smith, S. Hur, S., Stock, A. and Leithead, W. (2015). Using Improved Power Electronics Modelling and Turbine Control to Improve Wind Turbine Reliability. IEEE Transactions on Energy Conversion, volume 30, issue 3, 1043-1051.

  • Hur, S. and Grimble, M. (2015). Robust Nonlinear Generalised Minimum Variance control and fault monitoring. International Journal of Control, Automation, and Systems, volume 13, issue 3, 547-556.

  • Kapoor, R., Radhacharan, C. and Hur, S. (2022). Machine Learning: A Key Towards Smart Cyber-Physical Systems. In book: Cyber-Physical Systems, pp.43-62, Chapter 3. 

  • Merz, Karl & Anaya-Lara, Olimpo & E. Leithead, William & Hur, Sung-ho. (2018). Supervisory Wind Farm Control. In book: Offshore Wind Energy Technology, pp.305-344, Chapter 8. 

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