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Dynamic multiobjective optimization for thrust allocation in ship application

机译:动态多目标优化船舶应用中的推力分配

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摘要

Thrust allocation is a key procedure in the dynamic position system (DPS) of marine vessels. The present work aims to study the characteristics of dynamic optimization in thrust allocation. A two-phase analysis process is proposed. In phase-I, the model for thrust allocation is generated from the viewpoint of multiobjective optimization. Fuel consumption and tear-and-wear on the thrusters are chosen as objectives. Multiobjective feasibility enhanced particle swarm optimization algorithm (MOFEPSO) is applied to find the Pareto set of this problem. An additional decision-making procedure, the technique of order preference by similarity to ideal solution (TOPSIS) is utilized to choose the final compromise solution in phase-II. The self-organizing map (SOM) technique is undertaken to mine the Pareto data set. A Remote Operated Vehicle (ROV) example is provided for illustrating the above analysis process. The effects of relative importance between objectives upon characteristics of thrust allocation are studied. The trajectories of decision variables and objectives are examined through the SOM method. Results from numerical examples demonstrate that the multiobjective optimization method together with decision-making skills can extend the application of optimization in the thrust allocation field. The findings in this work add to the understanding of relationships among several aspects of DPS.
机译:推力分配是海洋船舶动态位置系统(DPS)的关键程序。目前的工作旨在研究推力分配的动态优化特征。提出了一种两相分析过程。在阶段I中,从多目标优化的观点来看,生成推力分配模型。选中推进器上的燃油消耗和撕裂和磨损作为目标。使用多目标可行性增强粒子群优化算法(MoFepso)应用于找到此问题的Pareto集。额外的决策程序,通过与理想解决方案(TOPSIS)相似的顺序偏好技术来选择阶段-II中的最终折变解决方案。进行了自组织地图(SOM)技术以挖掘Pareto数据集。提供远程操作的车辆(ROV)示例,用于说明上述分析过程。研究了目标对推力分配特征对象之间的相对重要性的影响。通过SOM方法检查决策变量和目标的轨迹。来自数值示例的结果表明,多目标优化方法与决策技能一起可以扩展到闪击分配领域的优化应用。这项工作中的调查结果增加了对DPS的几个方面之间的关系。

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