Adaptive NN-SM Control for Path Following of Underactuated Surface Vessels

doi:10.16183/j.cnki.jsjtu.2019.122

Abstract

Abstract:

A control method combining the neural network (NN) and sliding mode (SM) is proposed for path following of underactuated surface vessels. The line-of-sight (LOS) guidance is used to solve the underactuated problem, and an adaptive state observer of drift angle is designed for counteracting the steady state cross-track error caused by the drift angle. The SM control method is applied to heading control while the NN is included to cope with the uncertainties of control model. The stability of the control system is proved by the Lyapunov theory, and the validity of the proposed controller is verified by comparing the simulation results.

Key words: surface vessel, path following, line-of-sight (LOS) guidance, adaptive observer, neural network (NN), sliding mode (SM) control

CLC Number:

TP273

HE Hongwei, ZOU Zaojian, ZENG Zhihua. Adaptive NN-SM Control for Path Following of Underactuated Surface Vessels[J]. Journal of Shanghai Jiaotong University, 2020, 54(9): 890-897.

Figures/Tables 5

References 15

[1]	HEALEY A J, LIENARD D. Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles[J]. IEEE Journal of Oceanic Engineering, 1993,18(3):327-339.
[2]	FREDRIKSEN E, PETTERSEN K Y. Global κ-exponential way-point maneuvering of ships: Theory and experiments[J]. Automatica, 2006,42(4):677-687.
[3]	FOSSEN T I, BREIVIK M, SKJETNE R. Line-of-sight path following of underactuated marine craft[J]. IFAC Proceedings Volumes, 2003,36(21):211-216.
[4]	LEKKAS A M, FOSSEN T I. Trajectory tracking and ocean current estimation for marine underactuated vehicles [C]//2014 IEEE Conference on Control Applications (CCA). Juan Les Antibes, France: IEEE, 2014: 905-910.
[5]	BORHAUG E, PAVLOV A, PETTERSEN K Y. Integral LOS control for path following of underactuated marine surface vessels in the presence of constant ocean currents [C]//IEEE Conference on Decision and Control. Cancun, Mexico: IEEE, 2008: 4984-4991.
[6]	KAHVECI N E, IOANNOU P A. Adaptive steering control for uncertain ship dynamics and stability ana-lysis[J]. Automatica, 2013,49(3):685-697.
[7]	FOSSEN T I, LEKKAS A M. Direct and indirect adaptive integral line-of-sight path-following controllers for marine craft exposed to ocean currents[J]. International Journal of Adaptive Control & Signal Processing, 2017,31(4):445-463.
[8]	LIU C, CHEN C P, ZOU Z, et al. Adaptive NN-DSC control design for path following of underactuated surface vessels with input saturation[J]. Neurocomputing, 2017,267:466-474.
[9]	刘洋, 郭晨. 船舶航向保持RBF神经网络自适应非线性控制[J]. 大连海事大学学报, 2013,39(4):1-4.
	LIU Yang, GUO Chen. RBF neural network based adaptive nonlinear control for ship course keeping[J]. Journal of Dalian Maritime University, 2013,39(4):1-4.
[10]	罗伟林, 邹早建, 李铁山. 基于神经网络和L2增益的船舶航向自动舵设计[J]. 中国造船, 2009,50(2):40-45.
	LUO Weilin, ZOU Zaojian, LI Teishan. Neural-network and L2-gain based autopilot design of ship course-keeping[J]. Shipbuilding of China, 2009,50(2):40-45.
[11]	秦梓荷, 林壮, 李平, 等. 基于LOS导航的欠驱动船舶滑模控制[J]. 中南大学学报(自然科学版), 2016,47(10):3605-3611.
	QIN Zihe, LIN Zhuang, LI Ping, et al. Sliding-mode control of underactuated ship based on LOS guidance[J]. Journal of Central South University (Science and Technology), 2016,47(10):3605-3611.
[12]	FOSSEN T I. Handbook of marine craft hydrodynamics and motion control[M]. New York: John Wiley & Sons, 2011: 1-596.
[13]	李铁山, 邹早建, 罗伟林. 基于DSC后推法的非线性系统的鲁棒自适应NN控制[J]. 自动化学报, 2008,34(11):1424-1430.
	LI Tieshan, ZOU Zaojian, LUO Weilin. DSC-backstepping based robust adaptive NN control for nonlinear systems[J]. Acta Automatica Sinica, 2008,34(11):1424-1430.
[14]	刘程. 船舶路径跟踪与减横摇综合控制研究[D]. 上海: 上海交通大学, 2015.
	LIU Cheng. Integrated control of path following and roll motion reduction for marine vessels[D]. Shanghai: Shanghai Jiao Tong University, 2015.
[15]	FOSSEN T I. Guidance and control of ocean vehicles[M]. New York: John Wiley & Sons, 1994: 1-494.