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

机译:实时系统的轨迹优化算法及其在FPGA上的实现

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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:近年来,随着太空活动的扩展,地球与太空之间的太空运输越来越活跃。九州工业大学空间系统实验室一直在进行亚轨道有翼火箭的开发项目,作为完全可重复使用的空间运输系统的搜索项目。提出了一种基于遗传算法(GA)的轨迹优化方法,并将其在现场可编程门阵列(FPGA)上实现,以用于机载实时制导系统,用于有翼火箭。在有飞行面积约束的有翼火箭的回程飞行阶段进行轨迹优化。遗传算法是一种通过利用生命演化系统来解决优化问题的算法。 GA的优点是可以进行全局搜索,但缺点是计算成本比其他数学编程要高得多。通过使用罚分方法,可以实现具有飞行区域约束的优化。为了提高搜索性能,比较了交叉方法和生成交替模型。通过在FPGA上的实现设计了一个板载实时计算系统,用户可以使用软件编码自由地连接LSI(大规模集成)中的布线。

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