Multi-tank Adaptive Scheduling Algorithm and Simulation for Ship Stability Realization

doi:10.16182/j.issn1004731x.joss.19-0552

Abstract

Abstract: Aiming at the influence of the oil tank on the floating state and stability of the ship, the multi-tank adaptive dispatching control algorithm to maintain the stability of the ship is studied. The automatic floating state adjustment simulation system of the ship is realized by the WinCC (Windows Control Center) configuration software. For the system architecture, the Boolean logic table is used to construct the connection relationships of the oil tanks, pumps and pipelines, and the amount of oil exchange between the cabins is calculated according to the floating equation, and the balance of the floating state in the oiling process of the tanker is achieved according to the adaptive optimal scheduling algorithm of the multivariate and multi-constraint. The simulation results show that the scheduling algorithm can effectively adjust the floating state of the ship and maintain the stability of the ship, and can avoid the adverse effects caused by the uneven distribution of oil volume in the oil tank to ensure the navigation safety.

Key words: ship stability, adaptive optimization, WinCC (Windows Control Center), tank scheduling

CLC Number:

TP391.9

Xiong Yong, Liang Xuanzhuo, Zhang Jia. Multi-tank Adaptive Scheduling Algorithm and Simulation for Ship Stability Realization[J]. Journal of System Simulation, 2020, 32(6): 1060-1070.

References

[1] 程虹, 李炜, 杨屹. 船舶浮态调整系统研究[J]. 中国造船, 2001, 42(1): 75-79.
Cheng Hong, Li Wei, Yang Yi. Research on ship floating state adjustment system[J]. Shipbuilding of China, 2001, 42(1): 75-79.
[2] 李建军. 大型油船安全控制技术的研究[D]. 上海: 上海海事大学, 2005.
Li Jianjun. Research on Safety Control Technology of Large Oil Tankers[D]. Shanghai: Shanghai Maritime University, 2005.
[3] 张建波, 强兆新, 郝金凤, 等. 超大型油船分舱方案优化设计研究[J]. 中国造船, 2017, 58(1): 125-134.
Zhang Jianbo, Qiang Zhaoxin, Hao Jinfeng, et al. Research on Optimization Design of Submarine Plan of Super Large Oil Tanker[J]. Shipbuilding of China, 2017, 58(1): 125-134.
[4] 谢田华. 船舶抗沉计算与决策模型研究[J]. 中国航海, 2005, 65(4): 11-14.
Xie Tianhua. Research on ship anti-sink calculation and decision model[J]. Navigation of China, 2005, 65(4): 11-14.
[5] 刘文艳. 综合试验舰浮态辅助决策系统研发[D]. 镇江:江苏科技大学, 2012.
Liu Wenyan. Development of Integrated Test Ship Floating State Assistant Decision System[D]. Zhenjiang: Jiangsu University of Science and Technology, 2012.
[6] 刘博. 基于三维模型的舰船浮态调整决策支持系统研究[D]. 大连: 大连海事大学, 2016.
Liu Bo. Research on Ship Floating State Adjustment Decision Support System Based on 3D Model[D]. Dalian: Dalian Maritime University, 2016.
[7] 王爱岭. 船舶破损进水浮态调整智能控制研究[D]. 镇江: 江苏科技大学, 2010.
Wang Ailing. Research on Intelligent Control of Ship's Damaged Influent Floating State Adjustment[D]. Zhenjiang: Jiangsu University of Science and Technology, 2010.
[8] 马鑫延. 舰船浮态调整实时仿真计算技术研究[D]. 大连: 大连海事大学, 2016.
Ma Xinting. Research on Real-time Simulation and Calculation Technology of Ship Floating State Adjustment[D]. Dalian: Dalian Maritime University, 2016.
[9] Panda D, Ramteke M. Preventive crude oil scheduling under demand uncertainty using structure adapted genetic algorithm[J]. Applied Energy (S0306-2619), 2019: 235.
[10] Fernandez-Viagas V, Framinan J M. A best-of-breed iterated greedy for the permutation flowshop scheduling problem with makespan objective[J]. Computers and Operations Research (S0305-0548), 2019: 112.
[11] Chiou J P, Chang C F, Jhang J S. Research for a New Novel Evolutionary Algorithm[C]. 2014 International Symposium on Computer, Consumer and Control. Taichung: Piscataway, NJ. 2014: 1115-1118.
[12] Yusoh Z I M, Tang M. Composite SaaS scaling in Cloud computing using a hybrid genetic algorithm[C]. 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing: Piscataway, NJ. 2014: 1609-1616.