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A nonlinear dynamic inversion-based neurocontroller for unmanned combat aerial vehicles during aerial refuelling

机译:基于非线性动态反转的无人战斗机空中加油神经控制器

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The paper presents the development of modelling and control strategies for a six-degree-of-freedom, unmanned combat aerial vehicle with the inclusion of the centre of gravity position travel during the straight-leg part of an in-flight refuelling manoeuvre. The centre of gravity position travel is found to have a parabolic variation with an increasing mass of aircraft. A nonlinear dynamic inversion-based neurocontroller is designed for the process under investigation. Three radial basis function neural networks are exploited in order to invert the dynamics of the system, one for each control channel. Modal and time-domain analysis results show that the dynamic properties of the aircraft are strongly influenced during aerial refuelling. The effectiveness of the proposed control law is demonstrated through the use of simulation results for an F-16 aircraft. The longitudinal neurocontroller provided interesting results, and performed better than a baseline nonlinear dynamic inversion controller without neural network. On the other hand, the lateral-directional nonlinear dynamic inversion-based neurocontroller did not perform well as the longitudinal controller. It was concluded that the nonlinear dynamic inversion-based neurocontroller could be applied to control an unmanned combat aerial vehicle during aerial refuelling.
机译:本文介绍了一种六自由度,无人作战飞机的建模和控制策略的发展,其中包括飞行中加油动作的直腿部分的重心位置行程。随着飞行器质量的增加,重心位置行程具有抛物线变化。基于非线性动态反转的神经控制器是针对正在研究的过程而设计的。为了反转系统的动力学,利用了三个径向基函数神经网络,每个控制通道一个。模态和时域分析结果表明,飞机的动态特性在空中加油过程中受到很大影响。通过使用F-16飞机的仿真结果,证明了拟议控制律的有效性。纵向神经控制器提供了有趣的结果,并且比没有神经网络的基线非线性动态反演控制器性能更好。另一方面,基于横向非线性动态反转的神经控制器的性能不如纵向控制器。结论是,基于非线性动态反转的神经控制器可应用于空中加油过程中的无人机控制。

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