Research Article
Improving the Control Performance of Jacking System of Jack-Up Rig Using Self-adaptive Fuzzy Controller Based on Particle Swarm Optimization
@INPROCEEDINGS{10.1007/978-3-031-08878-0_13, author={Tien-Dat Tran and Viet-Dung Do and Xuan-Kien Dang and Ba-Linh Mai}, title={Improving the Control Performance of Jacking System of Jack-Up Rig Using Self-adaptive Fuzzy Controller Based on Particle Swarm Optimization}, proceedings={Industrial Networks and Intelligent Systems. 8th EAI International Conference, INISCOM 2022, Virtual Event, April 21--22, 2022, Proceedings}, proceedings_a={INISCOM}, year={2022}, month={6}, keywords={Hydrodynamic amplification Environmental forces Fuzzy particle swarm optimization Jacking system}, doi={10.1007/978-3-031-08878-0_13} }- Tien-Dat Tran
Viet-Dung Do
Xuan-Kien Dang
Ba-Linh Mai
Year: 2022
Improving the Control Performance of Jacking System of Jack-Up Rig Using Self-adaptive Fuzzy Controller Based on Particle Swarm Optimization
INISCOM
Springer
DOI: 10.1007/978-3-031-08878-0_13
Abstract
Oil and gas Jack-up Rig is a type of offshore production for exploitation with complex structure and working modes, capable of operating independently at sea. Although Vietnam has rich petroleum resources, the exploitation equipment, particularly jack-up rigs, almost depends on international technologies. Therefore, the subject of an advanced control theory for the jacking system of Jack-up Rig is a critical issue. In this work, we study the Particle swarm optimization approach based on a Fuzzy controller to adapt to the effects of environmental forces and hydrodynamic amplification. The designed Fuzzy Particle Swarm Optimization controller is compared with the Fuzzy Proportional Integral Derivative controller in order to verify the advantage of the proposed method. By using Matlab software, the simulation results show the advantages of the suggested approach.
