Abstract
This paper is concerned with the robust path-following control problem for a class of perturbed unmanned marine systems with prescribed performance under the influence of perturbations which are composed by external disturbances and parametric uncertainties. In order to withstand the negative impacts of perturbations, a novel nonlinear extreme learning machine (ELM)-based estimator is presented to estimate the perturbations. On the basis of the estimation results, a robust perturbation rejection control scheme is developed to ensure the following errors of the unmanned marine system reducing into a predefined region by devising a decaying variable. The asymptotic path-following result of the unmanned marine system is concluded by Lyapunov stability theory, as well as the prescribed performance is ensured by employing the decaying variable. Finally, simulations verify the effectiveness of the proposed nonlinear ELM estimator-based perturbation rejection control technique.
