AUV Trajectory Tracking Models and Control Strategies: A Review

Abstract

Autonomous underwater vehicles (AUVs) have been widely used to perform underwater tasks. Due to the environmental disturbances, underactuated problems, system constraints, and system coupling, AUV trajectory tracking control is challenging. Thus, further investigation of dynamic characteristics and trajectory tracking control methods of the AUV motion system will be of great importance to improve underwater task performance. An AUV controller must be able to cope with various challenges with the underwater vehicle, adaptively update the reference model, and overcome unexpected deviations. In order to identify modeling strategies and the best control practices, this paper presents an overview of the main factors of control-oriented models and control strategies for AUVs. In modeling, two fields are considered: (i) models that come from simplifications of Fossen’s equations; and (ii) system identification models. For each category, a brief description of the control-oriented modeling strategies is given. In the control field, three relevant aspects are considered: (i) significance of AUV trajectory tracking control, (ii) control strategies; and (iii) control performance. For each aspect, the most important features are explained. Furthermore, in the aspect of control strategies, mathematical modeling study and physical experiment study are introduced in detail. Finally, with the aim of establishing the acceptability of the reported modeling and control techniques, as well as challenges that remain open, a discussion and a case study are presented. The literature review shows the development of new control-oriented models, the research in the estimation of unknown inputs, and the development of more innovative control strategies for AUV trajectory tracking systems are still open problems that must be addressed in the short term.

Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles

“…The path following navigation ensures that the vehicle follows a desired path to reach its destination, which is geometrically defined in Cartesian coordinates [10]. In the trajectory tracking problem, the vehicle must follow a time-parametrized path, meaning it must go to a certain point in a given time [11]. The integration of time and space restrictions makes trajectory tracking the most complex of the referred autonomous navigation methods.…”

A Tracking Algorithm for Sparse and Dynamic Underwater Sensor Networks

“…The application of UWSN relies heavily on the fusion of state estimation results from multiple sources in different sensor nodes. Nowadays, the fusion methods applied in UWSN can be divided into centralized and distributed schemes [4][5][6]. The centralized technique requires a fusion center to collect the measurement information of all other sensor nodes under the premise of reliable communication in UWSN.…”

Consistent Extended Kalman Filter-Based Cooperative Localization of Multiple Autonomous Underwater Vehicles

“…Due to the attenuation of underwater GPS signals and the complex marine environment, it is a challenge for autonomous underwater vehicles (AUV) to obtain high positioning accuracy [1]. Traditional acoustic-based positioning technologies, including long baseline (LBL), short baseline (SBL) and ultra-short baseline (USBL), are often limited by the operating area, acoustic beacon array arrangement, etc.…”