Abstract :
Ship course control is closely related with navigation security, maneuverability and economy. In the paper, based on backstepping algorithm, a hybrid intelligent controller is proposed to ship steering control. The controller is a nonlinear controller in nature, whose design is simpler and more intuitive than its linear counterparts. For the adaptive laws of the controller are derived in the sense of Lyapunov function, the stability can be guaranteed. With the advantages of intelligent algorithms, RBF neural network and reinforcement learning algorithm, which are utilized in this paper, the controller can overcome the influence of the wind, wave and flow, the uncertainty of the ship steering, and the limitation that accurate data are hard to get for the disturbance and the error in instrument measuring. At last, the results of the simulation show that the ship course can be properly controlled when changeable wind and wave exist and the accurate data can´t be obtained
Keywords :
Lyapunov methods; adaptive control; intelligent control; learning (artificial intelligence); neurocontrollers; nonlinear control systems; radial basis function networks; ships; stability; steering systems; Lyapunov function; RBF neural network; backstepping approach; controller adaptive laws; hybrid intelligent ship steering controller; nonlinear controller; reinforcement learning; ship course control; ship steering control; Adaptive control; Backstepping; Intelligent networks; Lyapunov method; Marine vehicles; Navigation; Neural networks; Programmable control; Security; Stability; Adaptive control; Backstepping control; RBF neural network; Reinforcement Learning; Ship steering control;
