Dynamic Positioning

2000 ◽  
pp. 111-119
Author(s):  
Aladdin Ayesh
Keyword(s):  
Dynamic Positioning

scholarly journals Performance of an Advanced Intelligent Control Strategy in a Dynamic Positioning (DP) System Applied to a Semisubmersible Drilling Platform

2021 ◽  
Vol 9 (4) ◽  
pp. 399
Author(s):  
Mohamad Alremeihi ◽  
Rosemary Norman ◽  
Kayvan Pazouki ◽  
Arun Dev ◽  
Musa Bashir
Keyword(s):  
Oil And Gas ◽  
Weather Conditions ◽  
Dynamic Positioning ◽  
System Failures ◽  
Oil Drilling ◽  
System A ◽  
Advanced Control ◽  
Safety And Reliability ◽  
Drilling Operations ◽  
Shallow Seas

Oil drilling and extraction platforms are currently being used in many offshore areas around the world. Whilst those operating in shallow seas are secured to the seabed, for deeper water operations, Dynamic Positioning (DP) is essential for the platforms to maintain their position within a safe zone. Operating DP requires intelligent and reliable control systems. Nearly all DP accidents have been caused by a combination of technical and human failures; however, according to the International Marine Contractors Association (IMCA) DP Incidents Analysis, DP control and thruster system failures have been the leading causes of incidents over the last ten years. This paper will investigate potential operational improvements for DP system accuracy by adding a Predictive Neural Network (PNN) control algorithm in the thruster allocation along with a nonlinear Proportional Integral derivative (PID) motion control system. A DP system’s performance on a drilling platform in oil and gas deep-water fields and subject to real weather conditions is simulated with these advanced control methods. The techniques are developed for enhancing the safety and reliability of DP operations to improve the positioning accuracy, which may allow faster response to a critical situation during DP drilling operations. The semisubmersible drilling platform’s simulation results using the PNN strategy show improved control of the platform’s positioning.

scholarly journals Dynamic Positioning using Deep Reinforcement Learning

2021 ◽  
Vol 235 ◽  
pp. 109433
Author(s):  
Simen Sem Øvereng ◽  
Dong Trong Nguyen ◽  
Geir Hamre
Keyword(s):  
Reinforcement Learning ◽  
Dynamic Positioning

scholarly journals Robustifying dynamic positioning of crane vessels for heavy lifting operation

2021 ◽  
pp. 1-13
Author(s):  
Jun Ye ◽  
Spandan Roy ◽  
Milinko Godjevac ◽  
Vasso Reppa ◽  
Simone Baldi
Keyword(s):  
Dynamic Positioning

scholarly journals Dynamic positioning of a sea vessel under the influence of a multi-harmonic external disturbance

2021 ◽  
Vol 1864 (1) ◽  
pp. 012153
Author(s):  
A. O. Vediakova ◽  
A. A. Vedyakov ◽  
V. S. Boev
Keyword(s):  
External Disturbance ◽  
Dynamic Positioning

DYNAMIC POSITIONING ℋ∞ CONTROLLER TUNING BY GENETIC ALGORITHM

2002 ◽  
Vol 35 (1) ◽  
pp. 349-354
Author(s):  
Decio C. Donha ◽  
Reza M. Katebi
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Positioning ◽  
Controller Tuning

Modeling and Simulation of Ship Motion for Dynamic Positioning Vessel

2014 ◽  
Vol 919-921 ◽  
pp. 2127-2130
Author(s):  
Pei Wen Yu ◽  
Hui Chen
Keyword(s):  
Modeling And Simulation ◽  
Wind Wave ◽  
Ship Motion ◽  
Dynamic Positioning ◽  
Positioning System ◽  
Dynamic Positioning System ◽  
Oil Supply ◽  
Mmg Model ◽  
Simulation Results

The paper presents a method to build MMG model of ship motion for a oil supply vessel (OSV) with dynamic positioning system. It is assumed that the ship motion exposed to environment disturbances like wind, wave & currents, The simulation results show that the model of the vessel and environment disturbances are suitable, and the method is practicable .

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