New Opportunities for Offshore Oil and Gas Platforms – Efficient, Effective, and Adaptable Facilities for Offshore Research, Monitoring, and Technology Testing

Satterlee, Kent; Watson, Stephanie; Danenberger, Elmer P.

doi:10.1109/oceans.2018.8604935

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…In the conception of jack-up and semi-submersible rigs, the JuR will always be preferred over a semi-submersible rig providing both are Many different types of offshore platforms have been developed depending on a variety of variables, including technical and scientific advancements, economics, the need to use deeper natural resources [9], [10], and disturbance limits [11]. Offshore solutions for the challenges include developing more high-speed technology and conducting more strong study efforts [12]- [14], whereas they need more costly expenditures and system design adjustments. Meanwhile, these solutions may be switched by content economically and task methodologies that can be maintained constant at the same time for cost savings, while still utilizing the same system architecture and meeting standards and laws.…”

Section: Introduction a Backgroundmentioning

confidence: 99%

Self-Adaptive Fuzzy Control Approach for Jack-up Rig Jacking System Based on Particle Swarm Optimization

Dang

Tran

et al. 2022

IEEE Access

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Many offshore projects, such as offshore oil and gas exploration and offshore wind farm development, have required controlling the position of elevating the hull in a stable and balanced manner in recent years. The Jack-up Rig (JuR) jacking control systems are a revolutionary innovation that is already being employed in offshore drilling and other maritime structures. The system is utilized automatically to control and stabilize the position of the JuR during sea state disturbances to keep platforms from being displaced. As a result, developing an improved control theory for the Jacking system (JS) of a JuR is very important. In this paper, First, we investigate how to adapt to the effects of external forces and hydrodynamic amplification using a particle swarm optimization strategy based on a fuzzy controller. Then, using the fuzzy controller as the foundation, we proposed the PSO -Self Adaptive Fuzzy Controller (PSO-SAFC) guaranteed by Lyapunov criteria and compares it with other fuzzy-based algorithms to show the benefit of adaptively and stability of the system. To verify the proposed algorithm, embedded STM32F746VG central processor used to build the algorithm and run Simulink models on Matlab, the collected data on the positions of the legs and the tilt compared it to the setting command values to move the Rig body and provided control signals to the Drive system. Eventually, the advantages of the proposed approach are demonstrated by the simulation and experiment outcomes.

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