PID compensating model for design of ship's autopilot

Kwon, Youngkuk; Park, Seonho; Lee, Jang-Myung

doi:10.1109/iccas.2016.7832486

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…However, this means that there is not enough attention paid to the subject and companies should provide the means to expand research in this area, so that they can implement sustainable policies at all levels, taking advantage of the transversality offered by the supply chain. [57,58,187,188] Unmanned vehicles [189][190][191][192] Automated Guided Vehicle System improvement [60,[193][194][195][196] Repairs, maintenance, and inspection [61][62][63][64][197][198][199][200][201][202] Vehicle systems improvement [203][204][205][206] Blockchain Applications of its use [65,207] Strengthening security [66,208] Energetic efficiency [67] Cybersecurity General considerations in the implementation of the technology [75,76,[208][209][210][211][212] Environmental risk reduction [73,213] Improving the safety of onboard systems [74] Horizontal [40,…”

Section: Discussionmentioning

confidence: 99%

Assessing Sustainability in the Shipbuilding Supply Chain 4.0: A Systematic Review

Ramírez-Peña

Fraga²,

Salguero

et al. 2020

Sustainability

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The supply chain is currently taking on a very important role in organizations seeking to improve the competitiveness and profitability of the company. Its transversal character mainly places it in an unbeatable position to achieve this role. This article, through a study of each of the key enabling technologies of Industry 4.0, aims to obtain a general overview of the current state of the art in shipbuilding adapted to these technologies. To do so, a systematic review of what the scientific community says is carried out, dividing each of the technologies into different categories. In addition, the global vision of countries interested in each of the enabling technologies is also studied. Both studies present a general vision to the companies of the concerns of the scientific community, thus encouraging research on the subject that is focused on the sustainability of the shipbuilding supply chain.

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Section: Discussionmentioning

confidence: 99%

Assessing Sustainability in the Shipbuilding Supply Chain 4.0: A Systematic Review

Ramírez-Peña

Fraga²,

Salguero

et al. 2020

Sustainability

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“…A number of authors are working out the methods that enable to reduce disadvantages of PID controller. For example, the findings of simulating a model of an autopilot with PID controller and a compensation device are shown in paper [3].They allow reducing overshooting, as well as turn away a vessel at a constant angular velocity. Paper [4] observes PID regulation used to control a vessel, however, the system includes a model for generating the path of the vessel heading taking into account the International Rules for Preventing Collisions at Sea (COLREG), especially modeled decision diagrams according to Rule 8 and 14 of COLREG.…”

Section: Introductionmentioning

confidence: 99%

A Marine Autopilot With a Fuzzy Controller Computed by a Neural Network

Sedova¹,

Sedov²,

Баженов³

et al. 2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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The paper proposes simulation findings for an autopilot IC-2005 on a signal simulator developed by the authors of an intelligent control system to steer a sea vessel. The principle of the intelligent control system operation consists of generating a data vector with values of the yaw angle of the vessel, the rate of the angle change, the rudder displacement values and the rate of angling the rudder blade change during the ship heading. The features of the seaway provided by current wind and wave conditions are defined through spectral analysis. Then the intelligent classifier of the control system selects the optimal pre-trained neural network model of the seaway from a series of them. The fuzzy logic controller settings are computed after that. 120 search patterns for six types of vessels in various navigation conditions were developed using the simulator as a result of modeling. 79 neural networks were trained, and 2518 neural network way models of them were obtained for a representative sample of search patterns. The top settings of neural networks to develop search pattern models of the seaways were identified in response to statistical manipulation. As exemplified by a trawler ship type, computer and simulation methods were carried out that proved the efficiency of the approach proposed to apply to an intelligent sea craft automatic heading control system Keywords-marine autopilot, fuzzy controller, neural network7th

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