Adaptive state-constrained trajectory tracking control of unmanned surface vessel with actuator saturation based on RBFNN and tan-type barrier Lyapunov function

To promote the vigorous development of the marine technology, more and more scientific research institutes have begun to develop unmanned surface vehicles (USVs) with advanced control performance. This paper addresses trajectory tracking problem for state-constrained USV under the influence of actuator saturation and general disturbance uncertainties. An anti-windup system with auxiliary variables is employed to cope with actuator saturation. Besides, full-state constrains are not violated by combining the tan-type barrier Lyapunov function and backstepping method. Moreover, RBFNN is adopted to approximate some unknown uncertain function terms. By utilizing adaptive estimation technique, the unknown upper boundaries of disturbance uncertainties, input saturation difference, as well as RBFNN approximation error are compensated. The semi-global asymptotic convergence is guaranteed by rigorous theoretical analysis and Lyapunov proof. Finally, simulations results are given to verify the feasibility of the proposed algorithm.

Automated summary

This paper addresses the trajectory tracking problem for state-constrained unmanned surface vehicles (USVs) under the influence of actuator saturation and general disturbance uncertainties. The proposed algorithm effectively controls the actuator saturation and disturbance uncertainties by utilizing the anti-windup system, RBFNN approximation, and adaptive estimation technique. The feasibility of the algorithm is verified through rigorous theoretical analysis and simulation results.