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Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider

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Recent Advances in Robotics and Automation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 480))

Abstract

This chapter presents a mathematical model and motion control analysis of a buoyancy-driven underwater glider. The glider mathematical model, which includes the presence of disturbance from the water currents, has been designed by using the Newton-Euler method. In order to predict and control the glider motion, a neural network control has been used as a model predictive control (MPC) as well as a gain tuning algorithm. The motion has been controlled by six control inputs: two forces of a sliding mass, a ballast pumping rate, and three velocities of water currents. The simulation results show the analysis of the motion control system for both neural network control approaches, and a comparison with the Linear Quadratic Regulator (LQR) controller is also included. The results show that the model is stable, and the neural network controller of MPC produced better control performance than the neural network gain tuner and the LQR, where the accuracy value of the MPC is 94.5 %.

“Based on Vertical motion simulation and analysis of USM underwater glider, Khalid Isa and Mohd Rizal Arshad which appeared in the Proceedings of the 5th International Conference on Automation, Robotics and Applications (ICARA 2011). © 2011 IEEE.”

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Acknowledgments

The author would like to thank the Malaysia Ministry of Higher Education (MOHE), ERGS-203/PELECT/6730045, Universiti Sains Malaysia (USM) and Universiti Tun Hussein Onn Malaysia (UTHM) for supporting the research.

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Authors and Affiliations

  1. Underwater Robotics Research Group (URRG), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia (USM), Nibong Tebal, 14300, Pulau Pinang, Penang, Malaysia

    Khalid Isa & M. R. Arshad

Authors
  1. Khalid Isa
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  2. M. R. Arshad
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Correspondence to Khalid Isa .

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Editors and Affiliations

  1. School of Engineering &, Advanced Technology (SEAT), Massey University, Private Bag 11 222, Palmerston North, 4442, New Zealand

    Gourab Sen Gupta

  2. , School of Engineering and Advanced Techn, Massey University, Private Bag 11 222, Palmerston North, 4442, New Zealand

    Donald Bailey

  3. , Saigon South Campus, RMIT International University, Nguyen Van Linh City 702, Ho Chi Minh City, 70000, Vietnam

    Serge Demidenko

  4. , School of Engineering and Computer Scien, Victoria University of Wellington, Wellington, 6140, New Zealand

    Dale Carnegie

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Isa, K., Arshad, M.R. (2013). Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider. In: Sen Gupta, G., Bailey, D., Demidenko, S., Carnegie, D. (eds) Recent Advances in Robotics and Automation. Studies in Computational Intelligence, vol 480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37387-9_2

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  • DOI: https://doi.org/10.1007/978-3-642-37387-9_2

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  • Print ISBN: 978-3-642-37386-2

  • Online ISBN: 978-3-642-37387-9

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