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Virtual Structure Formation Control via Sliding Mode Control and Neural Networks

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Advances in Neural Networks - ISNN 2017 (ISNN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

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Abstract

In this paper, a sliding mode controller is presented for the trajectory tracking by a group of ships with an established formation along a given parametrized path via neural network and sliding mode control technique. The control objective for each ship is to keep its relative positon in the formation while a virtual Formation Reference Point (FRP) tracks a predefined path. We first solve the virtual structure formation problems via sliding mode control method due to its excellent adaptability to external disturbance and system perturbation. Moreover, a radial basis function NN is considered in the design of the controller to approximate the unknown uncertainties efficiently. Some simulations are given to verify the theoretical results in this paper.

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Acknowledgements

This work is supported in part by the National Natural Science Foundation of China (Grant Nos: 61572540, 51179019, 51279106, 61374114), the Macau Science and Technology Development under Grant 008/2010/A1 and UM Multiyear Research Grants, the Fundamental Research Program for Key Laboratory of the Education Department of Liaoning Province (LZ2015006), the Fundamental Research Funds for the Central Universities under Grants 3132016313 and 3132016311.

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Authors and Affiliations

  1. Navigation College, Dalian Maritime University, Dalian, China

    Qi Qin, Tie-Shan Li & Cheng Liu

  2. Department of Computer and Information Science, University of Macau, Macau, China

    C. L. Philip Chen

  3. Department of Control Science and Engineering, Dalian University of Technology, Dalian, China

    Min Han

Authors
  1. Qi Qin
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  2. Tie-Shan Li
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  3. Cheng Liu
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  4. C. L. Philip Chen
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  5. Min Han
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Corresponding author

Correspondence to Tie-Shan Li .

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Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Qin, Q., Li, TS., Liu, C., Philip Chen, C.L., Han, M. (2017). Virtual Structure Formation Control via Sliding Mode Control and Neural Networks. 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_13

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  • DOI: https://doi.org/10.1007/978-3-319-59081-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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