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A Novel Architecture for Civil Aviation Aircraft Intelligent Landing using Dual Fuzzy Neural Network

机译:采用双模模糊神经网络的民航飞机智能着陆的新型建筑

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This paper presents a novel architecture of intelligent landing control of an airplane using dual fuzzy neural networks, including roll control, pitch control and altitude hold control. The neural network control has been implemented in MATLAB and the data for training have been taken from Flight Gear Simulator. The flight performance has been shown in the Flight Gear Simulator. The objective is to improve the performance of conventional landing, roll, pitch and altitude hold controllers. Simulated results show that control for different flight phases is successful and the neural network controllers provide the robustness to system parameter variation.
机译:本文介绍了使用双模糊神经网络的飞机智能着陆控制的新建筑,包括滚动控制,俯仰控制和高度保持控制。神经网络控制已在MATLAB中实现,并且已从飞行齿轮模拟器中取出培训数据。飞行齿轮模拟器的飞行性能已显示。目的是提高传统着陆,卷,间距和高度保持控制器的性能。模拟结果表明,不同飞行阶段的控制成功,神经网络控制器为系统参数变化提供了鲁棒性。

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