飞行航迹动态逆跟踪控制的神经网络方法

Flight Path Control by Full Nonlinear Dynamic Inversion Using Artificial Neural Networks

针对用动态逆方法设计飞行控制系统在极慢模态设计过程中所遇到的完全非线性问题 ,以及飞行器在执行低空突防任务时所面临的速度无法精确控制的条件 ,提出了一种以前向神经网络为核心的解决方案。文中给出了神经网络的拓朴结构、样本采集方法以及动态逆控制器的构造方法 ,仿真结果表明 ,该方案具有良好的指令跟踪能力。

Artificial neural networks are used to deal with both the full nonlinearity dynamics and the situation in which the flight velocity cannot be precisely regulated when the aircraft is in low altitude penetration. Full nonlinear dynamics is a key problem while designing the nonlinear dynamic inversion controller to control the flight heading angle and flight path angle. Simplication of the dynamic equations of a very slow loop is presented. The full nonlinear inverse mapping is proved to exist in a range of flight condition and can be approximated by feed forward neural networks. A scheme is used to construct the feed forward neural network controller including topology, sampling and training. Simulational results demonstrate that this controller works well.