Data-Driven Output Regulation of Uncertain 6 DOF AUV via Lagrange Interpolation

Abstract

This article proposes a data-driven method for tracking control of the autonomous underwater vehicle (AUV) with matched disturbances and time-varying model’s uncertain parameters. The method is established by combining the conventional model reference control principle with a corresponding procedure for step-wise updating controller parameters so that the model error between the AUV and an appropriately chosen linear stable model converges to zero. The update procedure of controller parameters is created based on Lagrange interpolation technique, hence it acts entirely on the experimentally collected data from the AUV. The expected tracking performance by using this proposed data-driven controller has been theoretically authenticated and through numerical simulation.