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Aircraft landing control based on fuzzy modeling networks

机译:基于模糊建模网络的飞机着陆控制

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Aircraft landing control based on fuzzy modeling networks are presented. The proposed scheme uses a fuzzy controller combined with a linearized inverse aircraft model. A multi-layered fuzzy neural network is used as the controller, it provides the control signals in each stage of the aircraft landing phase. The algorithm used to train the network is the back:propagation through time. The linearized inverse aircraft model provides the error signals which will be used to back propagate through the controller in each stage. The objective of this study is to improve the performance of conventional automatic landing systems. The simulation results are described for the automatic landing system of a commercial airplane. Tracking performance and robustness are demonstrated through software simulations. Simulation results show that the fuzzy controller can successfully expand the safety envelope to include more hostile environments such as severe turbulence.
机译:提出了基于模糊建模网络的飞机起降控制。所提出的方案使用模糊控制器和线性化的逆飞机模型相结合。多层模糊神经网络用作控制器,它在飞机着陆阶段的每个阶段提供控制信号。用于训练网络的算法是时间反向传播。线性逆飞机模型提供了误差信号,该误差信号将用于在每个阶段中通过控制器向后传播。这项研究的目的是提高常规自动着陆系统的性能。描述了商用飞机自动着陆系统的仿真结果。跟踪性能和鲁棒性通过软件仿真得到证明。仿真结果表明,模糊控制器可以成功地扩大安全范围,使其包含更恶劣的环境,例如剧烈的湍流。

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