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A method for predicting aircraft flying qualities using neural networks pilot model

机译:基于神经网络飞行员模型的飞机飞行质量预测方法

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This paper proposes a method for predicting aircraft flying qualities according to Cooper-Harper rating scale, where neural networks model is used to describe the nonlinear characteristics of pilot control based on experimental data. The relationship between the Cooper-Harper pilot rating and characteristics of a closed-loop aircraft-pilot system is investigated according to the parameters of pilot control error of closed-loop systems and pilot model phase lag. A large number of simulation results have been used to derive a numerical method that will effectively predict the aircraft flying qualities, and the new method has been validated independently using five different aircraft configurations.
机译:本文提出了一种基于库珀-哈珀定级尺度的飞机飞行质量预测方法,其中神经网络模型用于基于实验数据描述飞行员控制的非线性特征。根据闭环系统的飞行员控制误差和飞行员模型相位滞后的参数,研究了库珀-哈珀飞行员额定值与闭环飞机飞行员系统特性之间的关系。大量的仿真结果已被用于推导能够有效预测飞机飞行质量的数值方法,并且该新方法已使用五种不同的飞机配置独立进行了验证。

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