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