Adaptive Path-Following Control for an Unmanned Surface Vessel Using an Identified Dynamic Model

This paper proposes a path-following control method for an unmanned surface vessel (USV) based on an identified dynamic model. To handle the USV dynamic model effectively, a three degree-of-freedom model is employed instead of a full nonlinear dynamic model and linearized at specific equilibrium condition. The linearized model is identified with real data from several experiments by utilizing a particle swarm optimization method. Then, based on the identified model, an adaptive control algorithm is proposed to follow several waypoints and velocity command. The proposed control method utilizes virtual control input, dynamic surface control method, and adaptive terms to handle matched and unmatched uncertainties simultaneously. The overall closed-loop stability is analyzed by introducing deadzone errors composed of tracking error and saturation function. Finally, some experiment with a remodeled commercial fishing boat are conducted and analyzed to validate the performance of the proposed methods.