Backstepping and input saturation based control design for ship course-keeping

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Journal of Dalian Maritime University ›› 2014, Vol. 40 ›› Issue (3) : 28-32.

LIN Yu¹, MIAO Baobin²

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Abstract

Based on the Lyapunov stability theory and the backstepping technique, a direct adaptive neural network controller was proposed for ship coursekeeping control in the presence of input saturation. The scheme proposed was constructed by combining backstepping technique and “minimum learning parameter” technique, so the computational burden of the algorithm could be reduced drastically and the algorithm is convenient to be implemented in applications. A stability analysis which is subject to the effect of input saturation constrains is conducted with the help of an auxiliary design system. The proposed NN based controller guarantees that all the closeloop signals are uniform ultimate bounded (UUB) and the output of system converges to a small neighborhood of the desired trajectory. Numerical simulations illustrate the effectiveness of the proposed algorithm.

Key words

ship / course control / input saturation / Backstepping / neural network / minimum learning parameter

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LIN Yu, MIAO Baobin. Backstepping and input saturation based control design for ship course-keeping[J]. Journal of Dalian Maritime University. 2014, 40(3): 28-32

References

［1］罗伟林, 邹早建, 李铁山. 船舶航向非线性系统鲁棒跟踪控制［J］. 控制理论与应用, 2009, 26(8):893-895.
LUO Wei-lin, ZOU Zao-jian, LI Tie-shan. Robust tracking control of nonlinear ship steering ［J］. Journal of Control Theory and Applications, 2009 26(8):893-895.(in Chinese)
［2］LI Tie-shan, WANG Dan, FENG Gang, et al. A DSC approach to robust adaptive NN tracking control for strictfeedback nonlinear systems［J］. IEEE Transactions on Systems, Man, and Cybernetics- Part B: Cybernetics, 2010,40 (3) : 915-927.
［3］王林, 陈楠, 高嵬. 基于Backstepping的船舶航向自适应滑模控制［J］.船电技术, 2012,32(4):16-18.
WANG Lin, CHEN Nan, GAO Wei. Adaptive sliding mode control based on backstepping for marine autopilot systems ［J］. Marine Electric & Electronic Technology,2012, 32(4):16-18.(in Chinese
［4］杜佳璐，郭晨. 控制增益未知的船舶航向非线性自适应跟踪控制［J］. 控制理论与应用，2005, 22(2)：315-320.
DU Jialu，GUO Chen. Nonlinear adaptive design for coursetracking control of ship without a priori knowledge of control gain ［J］. Journal of Control Theory & Applications, 2005, 22(2): 315-320.(in Chinese)
［5］CHEN M, GE S S, HOW B V E. Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities［J］. IEEE Transactions on Neural Networks, 2010,21 (5): 796-812.
［6］KWAN C, LEWIS F L. Robust backstepping control of nonlinear systems using neural networks［J］. IEEE Transactions on Systems, Man, and CyberneticsPart A: Systems and Humans, 2000,30 (6): 753-766.
［7］ PENG Z H, WANG D, LAN W Y, et al. Robust leaderfollower formation tracking control of multiple underactuated surface vessels［J］. China Ocean Engineering, 2012, 26 (3): 521-534.
［8］ LUO W L, ZOU Z J. Neural network based robust control for trajectory tracking of underwater vehicle［J］. China Ocean Engineering, 2007, 21 (2):281-292.
［9］ YANG Y S, REN J S. Adaptive fuzzy robust tracking controller design via small gain approach and its application［J］. IEEE Trans Fuzzy Syst, 2003,11 (6) :783-795.
［10］ YANG Y S, FENG G, REN J S. A combined backstepping and small gain approach to robust adaptive fuzzy control for strictfeedback nonlinear systems［J］. IEEE Trans Syst, Man, Cybern A, Syst, Humans, 2004,34 (3): 406-420.
［11］李俊方，李铁山. 考虑输入饱和的直接自适应神经网络跟踪控制［J］. 应用科学学报，2013, 31(3): 294-302.
LI Jun-fang, LI Tie-shan. Direct adaptive neural network tracking control with input saturation ［J］. Journal of Applied Sciences, 2013, 31(3): 294-302.(in Chinese)
［12］WEN Changyun, ZHOU Jing, LIU Zhitao, et al. Robust adaptive control of uncertain nonlinear systems in the presence of input saturation and external disturbance ［J］. IEEE Transactions on Automatic Control, 2011 56(7):1672-1678.