改进的BP神经网络在飞机防滑刹车系统的应用

为了在飞机刹车过程中防止打滑和取得最佳刹车效果,提出用BP神经网络构造S_p(最佳滑移率)识别器.为了提高神经网络的学习能力,介绍一种学习步长自适应方法--二阶步长法,讨论了二阶步长法在实际应用中的一些问题并提出了解决方案.在二阶步长法基础上提出了三阶步长法.还提出了合理配置活化函数的方法.综合以上方法对BP算法加以改进,使学习精度和速度都大大提高.

Improved BP neural network in design of aircraft antiskid braking system

The construction of S p (perfect slip ratio) identifier with back-propagation neural network was proposed to prevent skidding and have the best braking effect in the aircraft braking process. In order to improve the learning ability of the network,a type of self-adaptive learning rate method,second-order learning rate method,was introduced. Some problems in the practice of this method were discussed and the solutions were presented. A third-order learning rate method was deduced based on the method. The method of reasonable configuration of active functions was proposed. The combination of these methods renders better learning precision and speed.