Jacking and energy consumption control over network for jack-up rig: simulation and experiment

• Autorzy: Do Viet-Dung , Dang Xuan-Kien , Tran Tien-Dat , Pham Thi Duyen-Anh

Identyfikatory

DOI

10.2478/pomr-2022-0029

• Języki publikacji: EN

Abstrakty

EN

Oil and gas projects differ from regular investment projects in that they are frequently large-scale, categorised as vital national projects, highly technological, and associated with significant risks. Drilling rigs are a crucial component of the oil and gas sector and the majority of the systems and equipment aboard drilling rigs are operated automatically. Consequently, it is crucial to address the topic of an advanced control theory for off-shore systems. Network technology connected to control is progressively being used to replace outdated technologies, together with other contemporary technologies. In this study, we examine how to adapt a networked control jacking system to the effects of internal and external disturbances with a time delay, using a Fuzzy controller (FC)-based particle swarm optimisation. To demonstrate the benefit of the proposed approach, the developed Fuzzy Particle Swarm Optimisation (FPSO) controller is compared with the fuzzy controller. Finally, the results from simulations and experiments utilising Matlab software and embedded systems demonstrate the suitability of the proposed approach.

Słowa kluczowe

EN

networked control system; environmental forces; energy consumption; Fuzzy Particle Swarm Optimization; jacking system; time-delay

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2022
• Tom: nr 3
• Strony: 89--98
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Do Viet-Dung

• Artificial Intelligent Transportation Research Group Ho Chi Minh City University of Transport Vietnam

• https://orcid.org/0000-0001-7581-2212

autor

Dang Xuan-Kien

• Artificial Intelligent Transportation Research Group Ho Chi Minh City University of Transport Vietnam

• https://orcid.org/0000-0002-5367-3992

autor

Tran Tien-Dat

• Artificial Intelligent Transportation Research Group Ho Chi Minh City University of Transport Vietnam

• https://orcid.org/0000-0001-7253-4536

autor

Pham Thi Duyen-Anh

• Artificial Intelligent Transportation Research Group Ho Chi Minh City University of Transport Vietnam
• Dong An Polytechnic, Vietnam

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).