船舶动力定位混合智能推力分配理论与方法研究

本项目以船舶动力定位的推力子系统为研究对象，针对复杂约束条件下实时准确推力分配的困难与问题，利用计算智能中两种新颖的智能优化算法-人工蜂群 (ABC)和生物地理学优化(BBO)算法，对船舶动力定位混合智能推力分配理论进行基础科学研究。本项目将研究基于ABC和BBO的混合智能优化分配理论与方法，具体研究内容包括：①建立包含推进器响应时间和推进效率的船舶动力定位推力分配数学模型；②探索ABC和BBO算法的搜索机理、工作性态及高性能算法策略；③研究基于ABC和BBO的混合算法统一框架、工作性态和高性能算法策略；④给出求解具有复杂约束条件的船舶动力定位推力分配的高性能混合算法。本项目的研究成果，不仅可以大大改善船舶动力定位中，具有复杂约束推力分配的实时性与准确性，丰富和深化已有的动力定位推力分配理论与方法，而且可以推广到解决其它具有约束条件的复杂优化问题，促进计算智能在船舶与海洋工程领域中的应用。

In order to solve the real-time problem and enhance the accuracy in thrust allocation for ship dynamic positioning system(DPS), the artificial bee colony(ABC) algorithm and biogeography-based optimization(BBO) algorithm are employed to solve thrust allocation in this project. The hybrid intelligent thrust allocation theory and method based on ABC and BBO are proposed via this project. The main research contents include: ①The thrust allocation mathematical model for DPS including thruster response time and propulsive efficiency is firstly established. ②The searching mechanism, working behavior and algorithms with high performance of ABC and BBO are explored. ③The unified framework, working behavior and algorithm with high performance of ABC-BBO hybrid algorithm are studied.④The high efficient hybrid algorithm of ABC and BBO for thrust allocation with complex constrained conditions in DPS is presented. The research output of this project will not only improve the performance of thrust allocation in DPS, but also can be served as an example for other complex optimization problems so that the applications of computational intelligence in ship & oceanic engineering is further promoted.