A time differences of arrival‐based homing strategy for autonomous underwater vehicles

Abstract

SUMMARYA new sensor-based homing integrated guidance and control law is presented to drive an underactuated autonomous underwater vehicle (AUV) toward a fixed target, in 3-D, using the information provided by an ultra-short baseline (USBL) positioning system. The guidance and control law is first derived at a kinematic level, expressed on the space of the time differences of arrival (TDOAs), as directly measured by the USBL sensor, and assuming the plane wave approximation. Afterwards, the control law is extended for the dynamics of an underactuated AUV resorting to backstepping techniques. The proposed Lyapunov-based control law yields almost global asymptotic stability (AGAS) in the absence of external disturbances and is further extended, keeping the same properties, to the case where known ocean currents affect the motion of the vehicle. Simulations are presented and discussed that illustrate the performance and behavior of the overall closed-loop system in the presence of realistic sensor measurements and actuator saturation.

A two‐step control approach for docking of autonomous underwater vehicles

“…In the end, the force along the surge axis and the torque are determined so that the surge speed and the angular velocities converge to the desired values, which in turn ensures that all errors converge to zero. The idea of setting a desired velocity first and then using the angular speed to achieve this goal has been used before, see, for example, , , and . The latter presents a path following algorithm for underactuated marine surface vessels, including the dynamics of the vehicle and known constant ocean currents.…”

“…The initial approach to the base, usually denominated as homing, is not considered in this paper, see , and references therein for further details on that subject. During the homing stage, the only purpose of the vehicle is to approach the vicinity of the base, without any particular attitude or direction of arrival.…”

Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone

“…Recently, autonomous marine vehicles have been greatly studied, which have been applied in different ocean engineering fields, such as seafloor mapping, maritime rescue, ocean sampling surveillance, and mine development and so forth 1‐17 . Therefore, many scholars have devoted themselves on the control problems of such systems 18‐25 .…”

Global Adaptive Neural Network Control of Underactuated Autonomous Underwater Vehicles with Parametric Modeling Uncertainty

“…For example, reference 9 utilized local linearization and decoupling of the multi-variable model. [8,[10][11][12][13] described how to use a backstepping technique to develop the controllers necessary to perform trajectory tracking or path following. A controller was derived in [14] by resorting to model-based design techniques.…”