Single-parameter-learning-based finite-time tracking control of underactuated MSVs under input saturation

This paper investigates the adaptive finite-time (FT) tracking control problem of underactuated marine surface vehicles (MSVs) subject to parameter uncertainties and external disturbances under input saturation. The input saturation nonlinearity is approximated employing Gaussian error function. Definition of hand position is extended to transform the original motion mathematical model of underactuated MSVs into the standard integral cascade form. The compounded uncertain vector synthesizing the uncertain parameters and unknown external disturbances is transformed into a linear parameterized form with a single parameter. Then, by employing the adaptive vector-backstepping design framework, a novel adaptive FT tracking control law is designed, and the estimation of the single unknown parameter is provided by an adaptive law online. Theoretical analysis shows that under the proposed tracking control scheme, FT convergence of position tracking errors of underactuated MSVs into a small set around the origin is ensured, while all signals in the closed-loop tracking control system are bounded. Simulation and comparison verify the effectiveness of the proposed novel adaptive tracking control scheme.