This chapter investigates the performances of different control schemes, from non-model-based (proportional-integral-derivative control, PID) to model-based (com-puted torque control, CT) as well as adaptive model-based (adaptive proportional-derivative plus control, APD+), implemented on a low-inertia underwater vehicle for three-dimensional (3D) helical trajectory tracking. Then, the asymptotic stability of the resulting closed-loop dynamics for each control scheme is proven based on the Lyapunov direct method. The performances of the control schemes, implemented on the Leonard underwater vehicle for 3D helical trajectory tracking, are then demonstrated through scenarios-based numerical simulations. The proposed simulations are conducted under the influences of the vehicle's buoyancy and damping changes, para-metric variations; sensor noise, internal vehicle's perturbations; and water current, external disturbances rejection. Moreover, we demonstrate the task of transporting an object by the vehicle during underwater missions. The obtained simulation results show the effectiveness and robustness of the APD+ control scheme for tracking control of the low-inertia underwater vehicle in marine applications, outperforming the other controllers.