Data-driven adaptive trajectory tracking control of unmanned marine vehicles under disturbances and DoS attacks

This article researches the trajectory tracking problem for unmanned marine vehicles (UMVs) with disturbances and under denial-of-services (DoS) attacks in the wireless channel. By applying the partial form dynamic linearization algorithm, an equivalent data-driven model of the UMVs with ocean disturbances is firstly established. And the disturbances are estimated by using extended state observer, which improves the immunity of the UMVs to disturbances in the environment, and the robustness of the UMVs systems is better. It is the first time that the DoS attacks are considered under the data model for UMVs, and a novel data-driven adaptive trajectory tracking control framework is constructed. When the proposed equivalent data model suffers from DoS attacks which follows the Bernoulli distribution, an attack predictive compensation mechanism is devised to relieve the influence of DoS attacks. Based on it, the data-driven adaptive trajectory tracking controller is designed such that the error of trajectory tracking is convergent under DoS attacks and external disturbances. Finally, the effectiveness of the proposed data-driven control scheme and the predictive compensation mechanism is validated through the simulations.