A robust adaptive fuzzy sliding mode controller for trajectory tracking of ROVs

This study deals with dynamic modeling and tracking control of a remotely underwater vehicle (ROV) with six degrees of freedom (DOF). The sliding mode scheme for tracking control of an ROV is a powerful approach to compensate structured and unstructured uncertainties. In this study, performance of sliding mode approach modified by robust adaptive fuzzy control algorithm for an ROV is presented. Fuzzy algorithm is used for on-line estimation of external disturbances as well as unknown nonlinear terms of dynamic model of the ROV. A robust control rule is employed to compensate for estimation errors. The boundedness and asymptotic convergence properties of the control algorithm and its semi-global stability are analytically proven using Lyapunov stability theory and Barbalat's lemma. Moreover, adaptation laws and robust control terms are derived from Lyapunov stability synthises. The adopted control scheme is implemented in numerical simulations, based on the dynamic parameters of Shiraz University Remotely Operated Vehicle (Ariana I ROV). Simulations show the effectiveness of the adopted controller for trajectory tracking.