Automatic Ship Berthing Based on Fuzzy Logic

Abstract

Because the maneuverability of ship at low speed is reduced significantly, ship berthing is one of most difficult duties that ship master usually has to face as arriving at the port. In order to make sure the safe accomplishment of ship berthing, all steps need to be performed properly. In fact of maritime safety, the tugboats and thrusters are commonly utilized to support crabbing motion of ship in final stage of berthing process before mooring. In addition, because of the nonlinear of ship dynamic on berthing, theories of artificial intelligence are suitable to mimic the actions of ship master in controlling ship berthing automatically. In this article, a support system is proposed to bring ship into berth automatically after using the maneuvering control system. Three fuzzy controllers are established for different tasks of the berthing algorithm. The first controller is designed to control the movement of ship in longitudinal direction toward to the normal of wharf with the ship's propeller, while the task of second controller is to stabilize the relative bearing error with tugboat. The final controller is responsible for bring the ship into wharf according to crabbing motion with bow thruster and tugboat simultaneously. Finally, numerical simulations are carried out to validate the performance of the proposed system. The results show that the berthing support system has good performance for ship.

Optimization-Based Automatic Docking and Berthing of ASVs Using Exteroceptive Sensors: Theory and Experiments

“…The first constraint (10b) ensures that the planned trajectory satisfies the kinematic and dynamic models of the vessel described by (1) and (2). The inequality constraint (10c) consists of the spatial constraints described in (8), as well as constraints on the maximum and minimum velocity, angular velocity, and thruster forces. The constraint in (10d) ensures that the slack variables are positive, and (10e) sets the initial state to that of the vessel.…”

“…One such approach to solving the docking problem is via fuzzy control. The control system is then based on fuzzy logic, and its behaviour changes based on a set of predetermined rules [6]- [8]. An other approach for docking, that has seen a lot of interest, is the use of Artificial Neural Networks (ANNs) [2], [5], [9]- [15].…”

Artificial Neural Network controller for automatic ship berthing: challenges and opportunities

“…The author tested the controller under a gust of wind from different directions, which is more realistic and also carried out real-time simulations to know the actual ship response under the proposed controller. Therefore, this work has been chosen together with a recent work done by Nguyen et al [39] , where he used Fuzzy logic to execute the crabbing motion. Nguyen et al [39] proposed three separate fuzzy controllers in this research.…”

“…Therefore, this work has been chosen together with a recent work done by Nguyen et al [39] , where he used Fuzzy logic to execute the crabbing motion. Nguyen et al [39] proposed three separate fuzzy controllers in this research. First is to control the longitudinal movement of ship normal to the pier by controlling propeller revolution; second is to minimize the bearing error by controlling tug, and third is to execute the crabbing motion by controlling bow thrusters and tug simultaneously.…”

Investigation of a Multitasking System for Automatic Ship Berthing in Marine Practice Based on an Integrated Neural Controller

“…However, this system has a drawback, in that the ship's motion in the longitudinal direction is assumed to be zero. On the other hand, Nguyen (2019) and Nguyen and Im [19,20] introduced fuzzy controllers for ship berthing in near areas of the berth. These systems can control the ship into the berth without any conditions, unlike previous studies.…”