Automatic Ship Berthing using Artificial Neural Network Based on Virtual Window Concept in Wind Condition

Ahmed, Yaseen Adnan; Hasegawa, Kazuhiko

doi:10.3182/20120912-3-bg-2031.00059

Cited by 23 publications

(31 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Chaos theory [161] (4) Support Vector Machine(SVM) [162] (5) Genetic Algorithm(GA) [ [186] The NN model has been considered as one of the most effective theories of automatic docking [87,119], which can learn and imitate the behavior of the human brain in the execution of ship docking stage. NN algorithm and PID controller are combined to design the new controller [60,88], which can resist high wind and wave disturbance [92]. This good effect is verified by simulation and experiment in the subsequent series of studies [89][90][91].…”

Section: Number Algorithm Number Algorithmmentioning

confidence: 75%

“…In addition, the combination of predictive algorithm and fuzzy control [80], PID algorithm [85], or the introduction of disturbance observer all adopt different methods to ensure ship stability [86]. The research on automatic docking and undocking control of ships is mainly based on the combination of neural network and PID [87][88][89][90][91][92].…”

Section: Stabilization Controlmentioning

confidence: 99%

“…At present, the optimization algorithm is applied to the optimization of PID control parameters. For example, ACA [66], GA [50,79], PSO algorithm [70] and NN algorithm [87][88][89][90][91][92]119] are applied to the controller to modify the PID parameters, which adapts to different operating conditions of ships and solves the problems of difficult adjustment of PID parameters and poor self-adaptation.…”

Section: Proportion Integral Derivative Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

View full text Add to dashboard Cite

At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

show abstract

Section: Number Algorithm Number Algorithmmentioning

confidence: 75%

Section: Stabilization Controlmentioning

confidence: 99%

Section: Proportion Integral Derivative Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

View full text Add to dashboard Cite

show abstract

“…Trajectory design is needed in automatic berthing control. Ahmed et al enabled a ship to navigate along an imaged route and stop at a given place 1.5 times the ship's length from the berth, which means they can complete the automatic berthing control task [6,7]. A value of 1.5 times the ship's length is set to allow sufficient maneuvering space to cope with any adverse situation, so berthing maneuvering does not necessarily bring the ship close to the berth but can also stop the ship at a certain distance outside the berth.…”

Section: Introductionmentioning

confidence: 99%

Research into the Automatic Berthing of Underactuated Unmanned Ships under Wind Loads Based on Experiment and Numerical Analysis

Piao

Guo

Sun

2019

JMSE

View full text Add to dashboard Cite

With the continuous improvement of unmanned ship automation requirements, research into the automatic berthing of underactuated unmanned ships has important theoretical significance and practical value. In order to determine the trajectory of unmanned ships, the line of sight (LOS) algorithm was applied due to the characteristics of underactuated unmanned ships without side thrusters. In order to resist wind disturbance, the active disturbance rejection control (ADRC) method was applied to keep the ship moving on its intended trajectory. Then, to carry out the simulation analysis before the tank experiment, a remote-control simulation system based on a user datagram protocol (UDP) communication was built, and the ability of the ADRC controller to make the ship perform completely automatic berthing in both wind and no wind conditions was verified in simulations. Combined with the simulation results, a tank experiment was accomplished at the Japanese National Research Institute of Fishery Engineering. The experimental results also showed that the ADRC controller has good robustness, that the problems of insufficient autonomous route determination and the disturbance rejection ability in the process of the automatic berthing of underactuated unmanned ships are solved, and the safety of ship navigation is improved, which lays a theoretical and experimental foundation for the further development of unmanned ship control.

show abstract

“…To eliminate such difficulties and to make the controller more robust, in this research the whole manoeuvring plan is divided into three basic elementary manoeuvres which are course changing, step deceleration and stopping. For course changing part, a new concept is used to ensure the consistency of the teaching data which is named as virtual window concept (Ahmed et al, 2012). Using this concept ships from any possible heading angle can make necessary course change to merge with the imaginary line well ahead from the berthing goal point.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Automatic Ship Berthing using Artificial Neural Network for Free Running Experiment

Ahmed

Hasegawa²

2013

IFAC Proceedings Volumes

Self Cite

View full text Add to dashboard Cite

Ship berthing has always considered as a multiple input multiple output phenomenon. And such controlling action becomes even more sophisticated when the ship approaches to a pier especially in low speed. The current and presence of wind also make the task more complicated. But, if a human brain can be replicated by any artificial intelligence technique to perform the same necessary action that human brain does, then automatic operation during complete berthing process is believed to be possible by many researchers. For that purpose as an initial stage of this research, artificial neural network is chosen as one of AI techniques for automatic berthing and to increase its learnability, concentration is given on the consistency of the teaching data provided. To do that, nonlinear programming method is used where ship's actual behavior is predicted using famous manoeuvring mathematical group model. After successfully training, ANN controller is tested for various known and unknown condition including wind disturbances and found good results. Finally, to verify the simulated successful results, the current research is based on execution of free running experiment with the implementation of automatic ship berthing using the same trained ANN where adequate decisions for command rudder and propeller revolution taken are decided automatically depending on real time multiple input parameters.

show abstract

Automatic Ship Berthing using Artificial Neural Network Based on Virtual Window Concept in Wind Condition

Cited by 23 publications

References 2 publications

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Research into the Automatic Berthing of Underactuated Unmanned Ships under Wind Loads Based on Experiment and Numerical Analysis

Implementation of Automatic Ship Berthing using Artificial Neural Network for Free Running Experiment

Contact Info

Product

Resources

About