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Neural-Network-Based Tracking Control of Offshore Steel Jacket Platforms

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Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration (ICSEE 2017, LSMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 763))

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Abstract

This paper deals with the problem of neural network tracking control for an offshore platform system under external wave forces. A feedforward backpropagation neural-network-based tracking controller (NNTC) is designed to attenuate the displacement response of the offshore platform. In the simulation, the proposed NNTC scheme can effectively improve the stability of the offshore platform. Furthermore, the designed NNTC is more robust than the feedforward and feedback optimal tracking controller (FFOTC) in terms of system parametric perturbations and external wave loads.

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Acknowledgments

This work was supported in part by the Natural Science Foundation of Zhejiang Province under Grant LQ12A01025 and the Natural Science Foundation of China under Grant 61379029.

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Authors and Affiliations

  1. China Jiliang University, Hangzhou, 310018, China

    Zhi-Hui Cai & Bao-Lin Zhang

  2. Ningbo Radio and TV University, Ningbo, 315016, China

    Xian-Hu Yu

Authors
  1. Zhi-Hui Cai
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  2. Bao-Lin Zhang
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  3. Xian-Hu Yu
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Corresponding authors

Correspondence to Zhi-Hui Cai or Bao-Lin Zhang .

Editor information

Editors and Affiliations

  1. Queen’s University Belfast, Belfast, United Kingdom

    Kang Li

  2. Nanjing Automation Research Institute, Nanjing, China

    Yusheng Xue

  3. Harbin Institute of Technology, Harbin, China

    Shumei Cui

  4. Shanghai University, Shanghai, China

    Qun Niu

  5. Queen’s University Belfast, Belfast, United Kingdom

    Zhile Yang

  6. Cranfield University, Bedford, United Kingdom

    Patrick Luk

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© 2017 Springer Nature Singapore Pte Ltd.

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Cai, ZH., Zhang, BL., Yu, XH. (2017). Neural-Network-Based Tracking Control of Offshore Steel Jacket Platforms. In: Li, K., Xue, Y., Cui, S., Niu, Q., Yang, Z., Luk, P. (eds) Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 763. Springer, Singapore. https://doi.org/10.1007/978-981-10-6364-0_29

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  • DOI: https://doi.org/10.1007/978-981-10-6364-0_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6363-3

  • Online ISBN: 978-981-10-6364-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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