Integrated navigation and control for a HAUV system using adaptive super-twisting sliding mode control and indirect Kalman filtering estimation

In this article, an integrated control and strap down inertial navigation system (SIDNS) is designed using the super-twisting algorithm (STA) and the extended indirect Kalman filter (EKF) for the hovering autonomous underwater vehicle system (HAUV). The 6-DOF nonlinear hydraulic dynamics of the HAUV are separated into the known and uncertainty terms to simplify controller design of the proposed STA system. An adaptive law is constructed to compensate uncertainty and the EKF algorithm is used to estimate the navigation information measured from INS-DVL (Doppler velocity log) and other supplementary sensors. Simulation for the integrated STA and SIDNS system shows the efficacy of the proposed method.