Appointed-time robust tracking control for uncertain unmanned underwater vehicles with prescribed performance

This article is concerned with the appointed-time robust tracking control problem for unmanned underwater vehicles (UUVs) with off-diagonal inertia matrices in the presence of model uncertainties, external disturbances, and unmeasured velocities. Specifically, a non-recursive strategy is introduced to develop a finite-time velocity observer (FTVO) for estimating the unmeasured velocities. Then, a new appointed-time prescribed performance control (APPC) scheme is designed to restrict both transient and steady-state performance of tracking errors within predetermined boundaries, wherein the appointed-time is independent of initial conditions and is preassigned offline in advance. By integrating the benefits of FTVO and APPC, a robust tracking control strategy combining the robust integral of the sign of the error (RISE) and the adaptive neural network approximation is developed to attenuate the lumped disturbances and guarantee asymptotic stability. The advantage of this strategy is that it can eliminate the requirements for the high-gain feedback and bounded time-derivatives of disturbances in comparison to conventional RISE works. The closed-loop system is proven to be uniformly ultimately bounded. Finally, simulation and experimental results verify the effectiveness of the proposed control method.