基于模糊神经网络的飞机防滑刹车系统研究

On Aircraft Antiskid Brake System Based on Fuzzy Neural Network

以某型飞机刹车系统为研究对象,为了使该系统以最佳滑移率工作,防止陷入深度打滑和获得最大的刹车结合系数,提出了一种智能飞机防滑刹车系统的设计方案,制定出刹车控制规律并对整个刹车系统进行了仿真。改进了现有飞机刹车防滑系统的控制算法,应用神经网络BP算法实时获取最佳滑移率,利用模糊神经网络实现快速逼近给定滑移率,并采用基于数字信号处理器(DSP)的硬件电路实现了智能刹车控制。实验结果表明,飞机防滑刹车效率有了明显改进,鲁棒性增强。

To prevent serious skidding and obtain maximum friction coefficient, a design of intelligent aircraft antiskid brake system is presented. The controlling algorithm is improved by employing some intelligence methods. The neural network BP algorithm is used to get the real-time perfect slip ratio, and the fuzzy neural network （FNN） method is used to follow up with the target slip ratio. The intelligent control is realized by using the circuit based on digital signal processor （DSP）. The result shows that the aircraft antiskid braking performance improves distinctly and the robust increase obviously.