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Proceedings of the 5th International Conference on Electrical Engineering and Automatic Control pp 1–8Cite as

Individual Pitch Control Based on Radial Basis Function Neural Network

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 367))

Abstract

As the increasing of structure in wind turbine (WT), the flapping vibration force of blade is more and more serious, and the output power will be unstable in operation of the merged power networks. In this paper, to improve the WT dynamic performance in running processes, by analyzing the WT aerodynamics, wind shear, and tower shadow effect, we have designed based on radial basis function neural network (RBFNN) control strategy for individual pitch control (IPC), using RBFNN approach pitch control system unknown nonlinear functions, and introduced into the adaptive law online adjustment the system error, to improve the dynamic performance of pitch control system and alleviate structure of fatigue loads. Finally, the results show that based on RBFNN for IPC produces adaptability dynamic performance. It can effectively improve power quality to reduce fatigue load in key components of WT.

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Author information

Authors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University, 410082, Changsha, China

    Bing Han, Zhiwen Zhang, Meng Tian & Ningfeng Deng

  2. College of Electrical and Information Engineering, Changsha University of Science & Technology, 410000, Changsha, China

    Lawu Zhou

Authors
  1. Bing Han
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  2. Lawu Zhou
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  3. Zhiwen Zhang
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  4. Meng Tian
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  5. Ningfeng Deng
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Corresponding author

Correspondence to Bing Han .

Editor information

Editors and Affiliations

  1. Robotics Institute, Harbin Institute of Technology, Weihai, China

    Bo Huang

  2. Robotics Institute, Harbin Institute of Technology, Weihai, China

    Yufeng Yao

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© 2016 Springer-Verlag Berlin Heidelberg

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Han, B., Zhou, L., Zhang, Z., Tian, M., Deng, N. (2016). Individual Pitch Control Based on Radial Basis Function Neural Network. In: Huang, B., Yao, Y. (eds) Proceedings of the 5th International Conference on Electrical Engineering and Automatic Control. Lecture Notes in Electrical Engineering, vol 367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48768-6_1

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  • DOI: https://doi.org/10.1007/978-3-662-48768-6_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48766-2

  • Online ISBN: 978-3-662-48768-6

  • eBook Packages: EngineeringEngineering (R0)

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