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Longitudinal Aircraft Parameter Estimation Using Neuro-Fuzzy and Genetic Algorithm Based Method

机译:基于神经模糊和遗传算法的纵向飞机参数估计

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Application of Adaptive Neuro Fuzzy Inference System (ANFIS) in conjunction with Genetic Algorithm (GA) optimization to the problem of aerodynamic modeling and parameter estimation for aircraft has been addressed in the current paper. A neuro fuzzy based GA optimizer capable of predicting generalized force and moment coefficients employing measured motion and control variables only, without the requirement of conventional variables or their time derivatives, is proposed. Furthermore, it is shown that such a model can be used to extract equivalent stability and control derivatives of a rigid aircraft. Results are presented for aircraft to showcase the applicability of the proposed algorithm for both modeling and estimation of longitudinal parameters.
机译:自适应神经模糊推理系统(ANFIS)与遗传算法(GA)优化与飞机的空气动力学建模问题和飞机参数估计相结合的应用。提出了一种神经模糊的GA优化器,其能够预测采用测量运动和控制变量的广义力和力矩系数,而不需要传统变量或其时间衍生物的要求。此外,示出这种模型可用于提取刚性飞机的等效稳定性和控制衍生物。为飞机提出了用于展示所提出的算法的适用性来展示纵向参数的建模和估计的应用。

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