Surge-varying LOS based path following of under actuated surface vehicles

1048-1055Subject to harsh ocean environment, a novel path following control scheme with accurate guidance and high anti-disturbance ability for under actuated surface vehicles is proposed. The innovative work is as follow: (1) Based on the traditional line-of-sight (LOS), a surge-varying LOS (SVLOS) guidance law is designed to achieve double guidance of speed and heading, which enhances the flexibility and precision of the previous LOS; (2) Unknown disturbances are exactly estimated by an exact disturbance observer (EDO), wherein the limitations of bounded and asymptotic observations can be avoided; (3) The EDO-based robust tracking controllers enable accurate disturbance compensation and guided signal tracking in harsh ocean environment. Rigorous theoretical analysis and significant simulation comparison have been done to demonstrate superiority of the EDO-SVLOS scheme

A Robust Model Predictive Control Approach for Autonomous Underwater Vehicles Operating in a Constrained workspace

This paper presents a novel Nonlinear Model Predictive Control (NMPC) scheme for underwater robotic vehicles operating in a constrained workspace including static obstacles. The purpose of the controller is to guide the vehicle towards specific way points. Various limitations such as: obstacles, workspace boundary, thruster saturation and predefined desired upper bound of the vehicle velocity are captured as state and input constraints and are guaranteed during the control design. The proposed scheme incorporates the full dynamics of the vehicle in which the ocean currents are also involved. Hence, the control inputs calculated by the proposed scheme are formulated in a way that the vehicle will exploit the ocean currents, when these are in favor of the way-point tracking mission which results in reduced energy consumption by the thrusters. The performance of the proposed control strategy is experimentally verified using a $4$ Degrees of Freedom (DoF) underwater robotic vehicle inside a constrained test tank with obstacles.Comment: IEEE International Conference on Robotics and Automation (ICRA-2018), Accepte

A review of path following control strategies for autonomous robotic vehicles: theory, simulations, and experiments

This article presents an in-depth review of the topic of path following for autonomous robotic vehicles, with a specific focus on vehicle motion in two dimensional space (2D). From a control system standpoint, path following can be formulated as the problem of stabilizing a path following error system that describes the dynamics of position and possibly orientation errors of a vehicle with respect to a path, with the errors defined in an appropriate reference frame. In spite of the large variety of path following methods described in the literature we show that, in principle, most of them can be categorized in two groups: stabilization of the path following error system expressed either in the vehicle's body frame or in a frame attached to a "reference point" moving along the path, such as a Frenet-Serret (F-S) frame or a Parallel Transport (P-T) frame. With this observation, we provide a unified formulation that is simple but general enough to cover many methods available in the literature. We then discuss the advantages and disadvantages of each method, comparing them from the design and implementation standpoint. We further show experimental results of the path following methods obtained from field trials testing with under-actuated and fully-actuated autonomous marine vehicles. In addition, we introduce open-source Matlab and Gazebo/ROS simulation toolboxes that are helpful in testing path following methods prior to their integration in the combined guidance, navigation, and control systems of autonomous vehicles

RBF-based supervisor path following control for ASV with time-varying ocean disturbance

1028-1036A robust model-free path following controller is developed for autonomous surface vehicle (ASV) with time-varying ocean disturbance. First, the geometrical relationship between ASV and virtual tracking point on the reference path is investigated. The differentiations of tracking errors are described with the relative motion method, which greatly simplified the direct differential of tracking errors. Furthermore, the control law for the desired angular velocity of the vehicle and virtual tracking point are built based on the Lyapunov theory. Second, the traditional proportional-integral-derivative (PID) controller is developed based on the desired velocities and state feedback. The radial basic function (RBF) neural network taking as inputs the desired surge velocity and yaw angular velocity is developed as the supervisor to PID controller. Besides, RBF controller tunes weights according to the output errors between the PID controller and supervisor controller, based on the gradient descent method. Hence, PID controller and RBF supervisor controller act as feedback and feed forward control of the system, respectively. Finally, comparative path following simulation for straight path and sine path illustrate the performance of the proposed supervisor control system. The PID controller term reports loss of control even in the unknown disturbance