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Tube-based explicit model predictive output-feedback controller for collective pitching of wind turbines

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  • Lasheen, Ahmed
  • Saad, Mohamed S.
  • Emara, Hassan M.
  • Elshafei, Abdel Latif

Abstract

Collective pitch control is the main tool used to regulate the speed and power of wind turbines while operating above their rated wind speeds. The main challenges that face collective pitch control designs are the constraints on the control actions, the unmodeled uncertainties, and the unmeasured system states. A tube – based explicit model-predictive output-feedback controller is designed to control the collective pitch angle. The proposed controller is capable of handling the constraints challenge, reducing the on-line computational time and producing the optimal control sequence. Furthermore, the proposed controller is robust against the unmodeled uncertainties. The challenge of unmeasured system states is eliminated since this is an output feedback controller. The performance of the proposed controller is compared to the performance of a gain-scheduled PI controller which is commonly adopted in industry. Simulation results through application to a typical 5-MW offshore wind turbine are obtained. Further, experimental results with hardware in loop are obtained for a reduced scale wind turbine model to demonstrate the feasibility of the controller for real time applications. Simulation and experimental results show the superiority of the proposed controller over the gain-scheduled PI controller.

Suggested Citation

  • Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2019. "Tube-based explicit model predictive output-feedback controller for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 131(C), pages 549-562.
    • Handle: RePEc:eee:renene:v:131:y:2019:i:c:p:549-562
    DOI: 10.1016/j.renene.2018.07.033
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    References listed on IDEAS

    as
    1. Lasheen, Ahmed & Elshafei, Abdel Latif, 2016. "Wind-turbine collective-pitch control via a fuzzy predictive algorithm," Renewable Energy, Elsevier, vol. 87(P1), pages 298-306.
    2. Jain, Achin & Schildbach, Georg & Fagiano, Lorenzo & Morari, Manfred, 2015. "On the design and tuning of linear model predictive control for wind turbines," Renewable Energy, Elsevier, vol. 80(C), pages 664-673.
    3. Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoon, 2017. "Model predictive control with finite control set for variable-speed wind turbines," Energy, Elsevier, vol. 126(C), pages 564-572.
    4. Odgaard, Peter Fogh & Larsen, Lars F.S. & Wisniewski, Rafael & Hovgaard, Tobias Gybel, 2016. "On using Pareto optimality to tune a linear model predictive controller for wind turbines," Renewable Energy, Elsevier, vol. 87(P2), pages 884-891.
    5. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2017. "Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines," Energy, Elsevier, vol. 118(C), pages 1222-1233.
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    Cited by:

    1. Li, Jianshen & Wang, Shuangxin & Li, Yaguang, 2020. "A model-free adaptive controller with tracking error differential for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 161(C), pages 435-447.
    2. Li, Jianshen & Wang, Shuangxin, 2021. "Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults," Renewable Energy, Elsevier, vol. 174(C), pages 293-304.

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