Automatic landing control using particle swarm optimization

J. Juang, B. Lin, Kuo-Chih Chin
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引用次数: 9

Abstract

This paper proposes an intelligent aircraft automatic landing controller that uses fuzzy-neural controller with particle swarm optimization to improve the performance of conventional automatic landing system. Control gains are selected by a parameter searching method called particle swarm theory. Comparisons on different control schemes are given. Simulation results show that the proposed automatic landing controller can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.
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基于粒子群优化的自动着陆控制
本文提出了一种基于模糊神经控制器和粒子群算法的智能飞机自动着舰控制器,以改善传统自动着舰系统的性能。通过粒子群理论的参数搜索方法选择控制增益。对不同的控制方案进行了比较。仿真结果表明,所提出的自动着陆控制器可以在不使用常规增益调度技术的情况下,成功地扩展飞机的安全包络线,使其适应强风扰动环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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