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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
China Jiliang University, Hangzhou, 310018, China
Zhi-Hui Cai & Bao-Lin Zhang
Ningbo Radio and TV University, Ningbo, 315016, China
Xian-Hu Yu
- Zhi-Hui Cai
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Correspondence toZhi-Hui Cai orBao-Lin Zhang.
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Editors and Affiliations
Queen’s University Belfast, Belfast, United Kingdom
Kang Li
Nanjing Automation Research Institute, Nanjing, China
Yusheng Xue
Harbin Institute of Technology, Harbin, China
Shumei Cui
Shanghai University, Shanghai, China
Qun Niu
Queen’s University Belfast, Belfast, United Kingdom
Zhile Yang
Cranfield University, Bedford, United Kingdom
Patrick Luk
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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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