LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Diving Adaptive Position Tracking Control for Underwater Vehicles

Photo from wikipedia

This paper presents a robust position tracking control scheme for underwater vehicles moving in a vertical plane. The idea comes from the demand of underwater position tracking control for the… Click to show full abstract

This paper presents a robust position tracking control scheme for underwater vehicles moving in a vertical plane. The idea comes from the demand of underwater position tracking control for the newly borne Trans-media Aerial Underwater Vehicle (TMAUV). Although position control of a TMAUV is still within the scope of autonomous underwater vehicles (AUVs) control, it has new features. An underwater reference path for the TMAUV could be characterized by a strong maneuver that many assumptions in the conventional AUV controller design could not be employed. In this paper, a Lyapunov-based backstepping controller is developed for a nonlinear coupled input system releasing all constraints on the pitch angle, heave velocity, and angular velocity. Furthermore, neural networks and parameter estimation are employed to develop a robust controller in the presence of model uncertainties, parameter uncertainties, and external disturbances. This paper also solves the problem of adaptive estimation for the system parameters under the coupled input condition. Simulations are presented to demonstrate the feasibility and effectiveness.

Keywords: control; underwater vehicles; tracking control; diving adaptive; position tracking; position

Journal Title: IEEE Access
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.