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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 30526

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Sliding Mode Control of Autonomous Underwater Vehicles
This paper describes a sliding mode controller for autonomous underwater vehicles (AUVs). The dynamic of AUV model is highly nonlinear because of many factors, such as hydrodynamic drag, damping, and lift forces, Coriolis and centripetal forces, gravity and buoyancy forces, as well as forces from thruster. To address these difficulties, a nonlinear sliding mode controller is designed to approximate the nonlinear dynamics of AUV and improve trajectory tracking. Moreover, the proposed controller can profoundly attenuate the effects of uncertainties and external disturbances in the closed-loop system. Using the Lyapunov theory the boundedness of AUV tracking errors and the stability of the proposed control system are also guaranteed. Numerical simulation studies of an AUV are included to illustrate the effectiveness of the presented approach.
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[1] Xu Yuru, Xiao Kun, “Technology development of autonomous ocean vehicle”, Journal of Automation, vol. 33, no. 5, pp.518-521, 2007.
[2] Xu Yuru, Pang Yongjie, Wan Lei, Sun Yushan, “AUV--state-of-the-art and prospect”, CAAI Transactions on Intelligent Systems, vol. 1, no. 1, pp.9-16, 2006.
[3] Yang Shi1. Weiqi Qian. “Adaptive Depth Control for Autonomous Underwater.Vehicles Based on Feedforward Neural Networks’’. Vol. 4 Issue 3, pp 107-118,2007.
[4] A. J. Healey and D. Lienard, “Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles,” IEEE Journal of Oceanic Engineering, vol. 18, no. 3, pp. 327-339, 1993.
[5] D. Xu, W. Yan, and Y. Shi, “Nonlinear variable structure double mode control of autonomous underwater vehicles,” Proc. IEEE International Symposium on Underwater Technology, pp. 425-430, Tokyo, May 23-26, 2000.
[6] Y. Nakamura, and S. Savant, “Nonlinear tracking control of autonomous underwater vehicles,” Proc. IEEE Int. Conf. on Robotics and Automation, vol. 3, pp. A4-A9, 1992.
[7] J. Nie, J. Yuh, E. Kardash, and T. I. Fossen, “Onboard sensor-based adaptive control of small UUVs in the very shallow water,” Proc. IFACControl Applications in Marine Systems, Fukuoka, Japan, pp. 201-206, 1998.
[8] N. Kato, “Applications of fuzzy algorithm to guidance and control of underwater vehicles,” Underwater Robotic Vehicles: Design and Control, J. Yuh (Ed.), TSI: Albuquerque, 1995.
[9] Huanan Yu, Jun Dai, “Control of autonomous underwater vehicle using fuzzy logic tuned by genetic algorithm” Journal of Harbin Engineering University, vol. 23, no. 5, pp.12-15, 2002.
[10] F.L.Lewis, S.Jagannathan and A. Yesildirek , “Neural Network Control of Robot Manipulators and Nonlinear systems”, Taylor & Francis , 1999.
[11] Ahmad Forouzantabar, Ahmadreza khoogar, mohammad javade fakharzadegan, “Controlling a New Biped Robot Model Since Walking Using Neural Network”,IEEE ICIT Conference, March 2007,Shenzhen, China.
[12] Xiao Liang, Yong Gan, Lei Wan, “Motion Controller for Autonomous Underwater Vehicle Based on Parallel Neural Network’’, International Journal of Digital Content Technology and its Applications, Vol 4, no 9, 2010.
[13] Ji-Hong Li, Pan-Mook Lee, Sang-Jeong Lee, “Motion control of an AUV using a neural network adaptive controller’’. Proceedings of the 2002 International Symposium on Underwater Technology, p p.217-221, 2002.
[14] A Forouzantabar, B Gholami, M Azadi, “Adaptive Neural Network Control of Autonomous Underwater Vehicles’’, International journal of Aerospace and Mechanical Engineering, issue 67, p: 304-309, 2012.
[15] T. Fossen. Guidance and Control of Ocean Vehicles. John Wiley and Sons, United States of America, 1995.
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[17] P. Ridao et al. Model identification of a low-speed uuv. In Control Applications in Marine Systems. International Federation on Automatic Control, 2001.
[18] Ahmad Forouzantabar, Ahmadreza khoogar, Ahmad Reza Vali, “Neural Network Control of a New Biped Robot Model with Back Propagation Algorithm”, IEEE RO-MAN 2007, August 26-29, Korea.
[19] Gonzalez, L.A. Design, modeling and control of an autonomous underwater vehicle). Bachelor of Engineering Honours Thesis. The University of Western Australia. 2004.
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