Automatic Ship Berthing Using Parallel Neural Controller

Im, Nam-Kyun; Hasegawa, Kazuhiko

doi:10.1016/s1474-6670(17)35058-9

Cited by 20 publications

(31 citation statements)

References 3 publications

(3 reference statements)

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“…After deciding the appropriate course by fuzzy reasoning, the course is corrected using a PD controller as shown in Equation 5 to correct the heading. (5) where, I  : desired heading calculated by fuzzy reasoning;  : ship's current heading;  : the yaw rate; KP : proportional gain; KD : differential gain.…”

Section: Controller Designmentioning

confidence: 99%

“…After him, ANN had been tried as a controller in different controlling aspects like temperature control, paper mill waste water treatment control, engine air/fuel ratio control, process control, arc welding control etc. In the field of berthing, after Hasegawa et al, [3] and Im et al, [4,5] had continued the research. Hasegawa proposed ANN combined with expert system to assist ANN, while Im proposed separate controllers instead of centralised one for command rudder and propeller revolution output respectively.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent Control for Ship Manoeuvering

Ahmed¹,

Hannan²,

Kamal³

2020

ARAM

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In ship manoeuvering, the only two actuators are rudder and propeller revolution for the whole system. Therefore, by controlling these two for a designated purpose, automation in ship manoeuvering could be established. Classical control system like PID for track keeping or course changing has widely been used by on-board autopilot system. However, there are number of sophisticated ship manoeuveres, where the classical control systems fail and thus, the intelligent controllers are often encouraged to take over the classical systems. This paper is aimed to point out the application of Artificial Neural Network (ANN) controller for automatic ship berthing and Fuzzy Logic controller for waypoint controller in particular. Strategies as well as the formation of the two controllers are discussed briefly. In addition, simulations and experiments results are presented and compared to ensure the practical applicability of these intelligent controllers.

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Section: Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent Control for Ship Manoeuvering

Ahmed¹,

Hannan²,

Kamal³

2020

ARAM

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“…When disturbance is considered for ship berthing, the teach- ing data needs to be reconstructed by a new berth maneuvering process, where the environmental conditions such as wind, current and wave are included. This work has been done by previous studies as in [2,6]. Therefore, this research only carry out the ship berthing system based on distance measurement system without considering the disturbances.…”

Section: Teaching Data Creation and Training The Neural Network In Ormentioning

confidence: 99%

“…The first research on artificial neural network (ANN) for automatic ship berthing was proposed by authors in [1] but this approach was then changed into expert system. After that, the use of neural network for automatic ship berthing has been continued by [2], where the authors suggested two parallel controllers instead of applying a centralized controller. The result obtained from this berthing system is excellent.…”

Section: Introductionmentioning

confidence: 99%

Development of Automatic Ship Berthing System Using Artificial Neural Network and Distance Measurement System

Nguyen

2018

IJFIS

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In the studies on an berthing control of ship, an artificial neural network (ANN) model is commonly employed as the main controller to control the rudder and the propeller. The existing ANN controllers that use the parameters consisting of the ship position and the ship heading as inputs cannot be applied to control automatically the ship into berth in different ports. To deal with this problem, the parameters, such as relative bearing and distance from ship to berth calculated by radar can be used as inputs for the controller. However, the calculation of these factors is not accurate because some errors arise on using radar for berthing process. This leads to the lack of confidence in ship berthing system using the parameters determined by radar. In this research, the neural network based-automatic berthing system is developed for ship by using the parameters which are measured by distance measurement system. By this proposed system, the ship is brought automatically into berth in different ports without retraining the neural network. In addition, this system guarantees that the parameters used for inputs of the neural network is measured exactly and continually. To validate the proposed algorithm, numerical simulations are carried out to two imaginary ports and a real port, and result showed the good performance of the proposed system for automatic ship berthing.

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“…After him, researchers continued to use ANN for temperature control, paper mill waste-water treatment control, process control etc. Hasegawa and Kitera [3] and Im and Hasegawa [4], [5] had continued their research on applying ANN for automatic ship berthing. However, the success was not up to mark as the controller often confused to navigate the ship up to the pier in wind disturbances.…”

Section: Introductionmentioning

confidence: 99%

An Artificial Neural Network Controller for Course Changing Manoeuvring

Ahmed¹,

Kamal²,

Hannan³

2019

IJITEE

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An Artificial Neural Network is a well-known AI technique for replicating human brain and offering suitable solution for any unpredictable complicated problem. Taking the advantage of it, this research will analyse the applicability of Neural Network Controller for ship manoeuvring, such as course changing. To train the controller, optimized teaching data are used to keep the consistency in the data as it could enhance the learning ability of the controller while training. A double layered feed-forward neural network and back propagation method are found suitable for this purpose. Later-on, simulations are done to justify the effectiveness of the trained controller for unknown situations

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Automatic Ship Berthing Using Parallel Neural Controller

Cited by 20 publications

References 3 publications

Intelligent Control for Ship Manoeuvering

Intelligent Control for Ship Manoeuvering

Development of Automatic Ship Berthing System Using Artificial Neural Network and Distance Measurement System

An Artificial Neural Network Controller for Course Changing Manoeuvring

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