Adaptive Neural Fixed-time Tracking Control of Underactuated USVs With External Disturbances

Abstract

This paper focuses on the fixed-time tracking control of underactuated unmanned surface vehicles (USVs) with environmental disturbances. An adaptive neural fixed-time control (ANFTC) scheme is proposed for tracking control of underactuated USVs. Neural network is introduced to approximate the unknown dynamics and external disturbances of USVs. Theoretical analysis proves that under the proposed control scheme, the controlled system can achieve the practical fixed-time stability and the tracking errors of the USV will converge to small neighbourhood of zero in fixed time independent on initial conditions. Finally, numerical simulations are carried out to demonstrate the effectiveness of the developed control strategy.