Adaptive Fuzzy Control of Autonomous Surface Vehicles for Fast Accurate Trajectory Tracking

This paper investigates the trajectory tracking control problem for the autonomous surface vehicles with unknown dynamics and environmental disturbances. A novel adaptive fuzzy constrained control approach is put forward to deal with this problem. Instead of the exponentially decaying functions, a new-type performance envelop is designed to offer a way to explicitly and freely preassign the settling time and the accuracy of trajectory tracking. Moreover, in lieu of involving the approach angle or azimuth angle, a new idea for tackling underactuation is proposed that yields a singularity-free continuous control solution. The fuzzy logic systems are employed to address the unknown and lumped nonlinearities in the closed-loop system. The resulting control system possesses inherent robustness to the external disturbances and the second derivative of the reference trajectory, thus without the need for employing disturbance observers or assuming the available derivative information. It is demonstrated by the constraint analysis based on dialectic by contradiction that the developed control achieves arbitrarily fast and accurate trajectory tracking for the vehicle. Finally, the effectiveness and superiority of our approach are verified by a comparative simulation.