Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method.
The problem of course control for underactuated surface ship is addressed in this paper. Firstly, neural networks are adopted to determine the parameters of the unknown part of ideal virtual backstepping control, even the weight values of neural network are updated by adaptive technique. Then uniform stability for the convergence of course tracking errors has been proven through Lyapunov stability theory. Finally, simulation experiments are carried out to illustrate the effectiveness of proposed control method.
College of Automation, Harbin Engineering University, Harbin 150001, China.
Junjia
J
Yuan
College of Automation, Harbin Engineering University, Harbin 150001, China.
Hao
H
Meng
College of Automation, Harbin Engineering University, Harbin 150001, China.
Qidan
Q
Zhu
College of Automation, Harbin Engineering University, Harbin 150001, China.
Jiajia
J
Zhou
D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D012767:Ships; D013997:Time Factors; D014186:Transportation