State recovery and disturbance estimation of unmanned surface vehicles based on nonlinear extended state observers

This paper investigates the state recovery and disturbance estimation of unmanned surface vehicles in the presence of unknown disturbances as well as unmeasured surge, sway, and yaw velocities. The disturbances come from the internal parametric model uncertainties, unknown hydrodynamics, and external disturbances due to wind, waves and ocean currents. At first, a nonlinear extended state observer is developed for not only recovering the unmeasured velocities, but also estimating the disturbances. By using simultaneous Lyapunov inequalities, the observer error dynamics is proven to be input-to-state stable. Then, a finite-time convergent nonlinear extended state observer is proposed to estimate the unknown velocities and disturbances, and the finite-time input-to-state stability of the observer error dynamics is established based on a homogeneous Lyapunov function. By using the proposed nonlinear extended state observers, both velocity and disturbance information can be reconstructed from the position-heading measurement by using global positioning system and gyrocompass only. Simulation results are provided to validate the efficacy of the proposed state recovery and disturbance estimation method for both fully-actuated and under-actuated unmanned surface vehicles.