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Trajectory Optimization Using Algorithm and Its Implementation on FPGA for Real Time System

机译:使用算法的轨迹优化及其在实时系统中的FPGA实现

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As the space activities expand in recent years, the space transportation between the earth and space is more and more activated. The Space Systems Laboratory of Kyushu Institute of Technology has been conducting suborbital winged rocket development project as a search project of fully reusable space transportation systems. This paper proposes a trajectory optimization method using Genetic Algorithm (GA) and its implementation on Field Programmable Gate Array (FPGA) to be applied to the winged rocket aiming at the onboard real time guidance system. The trajectory optimization is performed on the return flight phase of the winged rocket with flight area constraint. GA is an algorithm to solve optimization problems by employing the evolution system of life. GA has an advantage that the global search is acceptable, but has a disadvantage that the calculation cost is extremely higher than the other mathematical programming. The optimization with flight area constraint becomes possible by the use of the penalty method. In order to increase the searching performance, the crossover method and the generation alternation models are compared. An onboard real-time calculation system is designed by the implementation on FPGA, which user can freely connect wiring in LSI (Large Scale Integration) using software coding.
机译:随着空间活动近年来扩展,地球和空间之间的空间运输越来越激活。九州理工学院的空间系统实验室一直在开展亚孔翅膀火箭发育项目,作为全部可重复使用的空间运输系统的搜索项目。本文提出了一种使用遗传算法(GA)的轨迹优化方法及其在现场可编程门阵列(FPGA)上的实现,以应用于针对板载实时引导系统的翼型火箭。在具有飞行区域约束的飞行火箭的返回飞行阶段执行轨迹优化。 GA是一种解决优化问题来解决优化问题的算法。 GA具有优势,即全球搜索是可以接受的,但具有缺点,即计算成本远高于其他数学编程。通过使用惩罚方法可以实现与飞行区域约束的优化。为了增加搜索性能,比较交叉方法和生成交替模型。在FPGA上的实现设计了板载实时计算系统,用户可以使用软件编码在LSI(大规模集成)中自由连接布线。

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