Line-of-Sight-Based Guidance and Adaptive Neural Path-Following Control for Sailboats

This paper addresses the issue of waypoints-based path-following control for sailboats. Based on the parameterized line-of-sight framework, a novel guidance principle for the sailboat is developed, which comprises the mechanisms to observe the crab angle and generate the reference heading angle. For the crab angle observation, the approach with double reduced-order extended state observers and a saturation operator is developed, which involves the consideration of the intense sway. For the heading angle generation, three modes are devised, i.e., the path-following mode, the characteristic tacking mode, and the gybing mode. Sign functions are employed to describe tacking and gybing maneuvers of the sailboat such that rational switching of the reference heading angle is guaranteed, and no linguistic command is required. Matching with the proposed guidance principle, an adaptive neural control law is thereafter developed with the outputs landing in rudder angles. The echo state networks (ESNs) are introduced to offset model uncertainties and environmental disturbances with minimum parameters learning. By introducing two time-varying systems, all the errors in the closed-loop system are proved to be semiglobal uniformly ultimate bounded. Finally, the effectiveness of the proposed scheme is testified in MATLAB simulation.