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首页> 外文期刊>International journal of intelligent robotics and applications >Research on attack angle tracking of high speed vehicle based on PID and FLNN neural network
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Research on attack angle tracking of high speed vehicle based on PID and FLNN neural network

机译:攻角跟踪研究的高速度基于神经网络PID和FLNN车辆

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摘要

A kind of pitch channel dynamic model of hypersonic aircraft considered with both the model of engine and the model of elastic shape is studied. A special typical flying point is chosen that the state of elastic shape is assumed to be constant and the engine is designed with a PID law to make the speed of aircraft close to a constant. Then a kind of hybrid controller based on FLNN neural network and PID control is designed to make the attack angle can converged to desired value. And the adoption of Taylor type FLNN neural network can make use of the form of air dynamic coefficient which is a function like Taylor series, so it has a good adaptive ability to compensate the uncertainties and unconsidered factors of hypersonic model. And the use of PID control law can make use of the advantage of traditional classic control theory and what is the most important of all is that the PID control can provide enough damp ratio to make the system stable enough. So the hybrid control strategy can integrate both advantage of neural network and PID control methods which is also testified by the detailed numerical simulation in the last part of this paper.
机译:一种俯仰通道的动态模型超音速飞机的模型的发动机和弹性形状的模型研究。这被认为是弹性状态的形状常数和发动机设计PID法律使飞机的速度接近常数。FLNN神经网络和PID控制设计攻角可以聚集所需的值。FLNN神经网络可以利用的形式空气动力系数是一个函数泰勒级数,因此它具有良好的自适应能力赔偿的不确定性和不重要的超音速模型的因素。控制律可以利用的优势传统经典的控制理论是什么最重要的是,PID控制可以提供足够的阻尼比进行系统足够稳定。利用神经网络和集成也证实了PID控制方法详细的数值模拟在过去本文的一部分。

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