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Fuzzy optimal swarm of autonomous aircrafts for target determination and convergence control system.

机译:自主飞机模糊最优群的目标确定与收敛控制系统。

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摘要

The thesis project proposes analytical and theoretical algorithms for a networked swarm of autonomous vehicles, such as those used in planet exploration, and to be used in target location determination and convergence, an algorithm of this type could be used in an Autonomous Stratospheric Aircraft (ASA), thus having the possibility of being used for the exploration of a planet as well as many other applications. Upon locating an unknown location of a specified target, the algorithm would then swarm and eventually converge upon the location. There are two similar, but fundamentally different algorithms proposed in this project. These algorithms are capable of locating and converging upon multiple targeted locations simultaneously. This project is inspired by the current thought of NASA in the search of life on Mars, which is "Follow the Water" [18], where the targeted location would be the targeted source of water. These algorithms make use of combining a modified Particle Swarm Optimization algorithm with fuzzy variables for increased intelligence.
机译:本项目提出了一种用于网络自动驾驶车辆群的分析和理论算法,例如用于行星探测的网络,并用于目标位置确定和收敛,这种算法可用于自动平流层飞机(ASA) ),因此有可能被用于探索行星以及许多其他应用。在找到指定目标的未知位置后,该算法将蜂拥而至,最终收敛于该位置。此项目中提出了两种相似但根本不同的算法。这些算法能够同时定位并收敛于多个目标位置。该项目的灵感来自于美国宇航局在火星上寻找生命的当前思想,即“跟随水” [18],目标位置将是目标水源。这些算法将改进的粒子群优化算法与模糊变量结合使用,以提高智能性。

著录项

  • 作者

    Richards, Zach D.;

  • 作者单位

    University of Denver.;

  • 授予单位 University of Denver.;
  • 学科 Applied Mathematics.;Engineering Robotics.;Engineering Aerospace.
  • 学位 M.S.
  • 年度 2009
  • 页码 109 p.
  • 总页数 109
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:16

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