Abstract
Neural networks (NN) are applied to the tracking control of a three-link manipulator attached to an autonomous underwater vehicle (AUV). Lyapunov design is employed to obtain the NN based robust controller. The interaction between the AUV and the manipulator is considered. Nonlinearity in the plant is compensated by NN based identification. To illustrate the validity of the proposed controller, numerical simulation is performed and the comparison between the NN based controller and a conventional proportional-derivative (PD) controller is conducted.
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Acknowledgments
This work was partially supported by the Special Item supported by the Fujian Provincial Department of Ocean and Fisheries (No. MHGX-16), the Special Item for University in Fujian Province supported by the Education Department (No. JK15003), and the Special Item supported by Fuzhou University (No. 2014-XQ-16).
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Luo, W., Cong, H. (2017). Robust NN Control of the Manipulator in the Underwater Vehicle-Manipulator System. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_10
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DOI: https://doi.org/10.1007/978-3-319-59081-3_10
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