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Feedback Linearization and Reaching Law Based Sliding Mode Control Design for Nonlinear Hydraulic Turbine Governing System

Author

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  • Bicheng Guo

    (Key Laboratory of Transients in Hydraulic Machinery, Ministry of Education, Wuhan University, Wuhan 430072, China)

  • Jiang Guo

    (Key Laboratory of Transients in Hydraulic Machinery, Ministry of Education, Wuhan University, Wuhan 430072, China)

Abstract

Hydropower as renewable energy has continually expanded at a relatively high rate in the last decade. This expansion calls for more accurate scheme design in hydraulic turbine governing system (HTGS) to ensure its high efficiency. Sliding mode control (SMC) as a robust control method which is insensitive to system uncertainties and disturbances raises interest in the application in HTGS. However, the feature of highly coupled state variables reflects the nonlinear essence of HTGS and SMC studies on the related mathematical model under certain fluctuations are not satisfied. In this regard, a novel SMC design with proportional-integral-derivative manifold is firstly applied to a nonlinear HTGS with a complex conduit system. In dealing with certain fluctuations in speed and load around the rated working condition, the proposed SMC is capable of driving the system to the desired state with smooth and light responses in aspects of the key state variables. The exponential reaching law and introduced boundary layer fasten the speed of converging time and suppress chattering. A necessary integral of sliding parameter added to manifold successfully reduces the latency caused by the anti-regulation feature of HTGS. Three operating scenarios are simulated compared with the PSO-PID method, and results imply that the proposed SMC method equips with accurate trajectory tracking ability and smooth responses. Finally, the strong robustness against system uncertainties is tested.

Suggested Citation

  • Bicheng Guo & Jiang Guo, 2019. "Feedback Linearization and Reaching Law Based Sliding Mode Control Design for Nonlinear Hydraulic Turbine Governing System," Energies, MDPI, vol. 12(12), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2273-:d:239609
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    References listed on IDEAS

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    Cited by:

    1. Yuqiang Tian & Bin Wang & Diyi Chen & Shaokun Wang & Peng Chen & Ying Yang, 2019. "Design of a Nonlinear Predictive Controller for a Fractional-Order Hydraulic Turbine Governing System with Mechanical Time Delay," Energies, MDPI, vol. 12(24), pages 1-16, December.
    2. Zaher Mundher Yaseen & Ameen Mohammed Salih Ameen & Mohammed Suleman Aldlemy & Mumtaz Ali & Haitham Abdulmohsin Afan & Senlin Zhu & Ahmed Mohammed Sami Al-Janabi & Nadhir Al-Ansari & Tiyasha Tiyasha &, 2020. "State-of-the Art-Powerhouse, Dam Structure, and Turbine Operation and Vibrations," Sustainability, MDPI, vol. 12(4), pages 1-40, February.
    3. Zou, Yidong & Hu, Wenqing & Xiao, Zhihuai & Wang, Yunhe & Chen, Jinbao & Zheng, Yang & Qian, Jing & Zeng, Yun, 2023. "Design of intelligent nonlinear robust controller for hydro-turbine governing system based on state-dynamic-measurement hybrid feedback linearization method," Renewable Energy, Elsevier, vol. 204(C), pages 635-651.
    4. Lisheng Li & Jing Qian & Yidong Zou & Danning Tian & Yun Zeng & Fei Cao & Xiang Li, 2022. "Optimized Takagi–Sugeno Fuzzy Mixed H 2 / H ∞ Robust Controller Design Based on CPSOGSA Optimization Algorithm for Hydraulic Turbine Governing System," Energies, MDPI, vol. 15(13), pages 1-31, June.
    5. Antonio T. Alexandridis, 2020. "Modern Power System Dynamics, Stability and Control," Energies, MDPI, vol. 13(15), pages 1-8, July.

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