Nonlinear Adaptive Control For Underactuated Surface Vessel Path Following

This paper mainly investigates the issues of path following adaptive nonlinear control for underactuated surface vessels. In practice, the parameters of ship model are usually uncertain and the disturbances of wind, wave and current must be dealed with. The following research have been completed in this dissertation.(1) For path following problem of underactuated surface vessels model of three degrees of freedom with parameter uncertainties and external disturbances, an RBF neural network based adaptive controller is proposed. Firstly the position error of the ground coordinate system is converted to the position error in the path coordinate system by using global nonlinear coordinate changes, using the derivative of the path parameter as an additional control, and designing a suitable filter of sway velocity, and then a neural network based adaptive controll is designed for control loop, filter loop and propulsion loop of underactuated surface vessels respectively, in which the desired forward speed can be adjusted online. Based on Lyapunov stability analysis the authors prove that all error signals of vessels path following closed-loop system are uniformly ultimately bounded. Simulation studies verify the effectiveness of the controller.(2) For path following problem of underactuated surface vessels model of three degrees of freedom with nonlinear damping parameters uncertain, an adaptive output feedback controller is proposed. Firstly a globally exponentially stable observer is designed by applying Lyapunov direct method, and then an adaptive output feedback controller, in which the desired forward speed can be adjusted online, is given by means of differential homeomorphism equivalent conversion and backstepping design method. Based on Lyapunov stability analysis the authors proved that all error signals of vessels path following closed-loop system asymptotically stable. Simulation studies verify the effectiveness of the controller.For the above about path following RBF neural network and output feedback based adaptive control for underactuated surface vessels have been vertified by simulation, which explain relevant nonlinear algorithms are effective.