基于BP神经网络的固体导弹耗尽关机姿态调制方法研究  

An Approach to Attitude Angle Adjustment of Solid Missiles under the Condition of Depleted Shutdown Based on BP Neural Network

作　　者：鲜勇[1] 李少朋[1] 李邦杰[1] 

机构地区：[1]第二炮兵工程大学七系,陕西西安710025

出　　处：《兵工学报》2015年第4期668-673,共6页Acta Armamentarii

摘　　要：针对固体火箭发动机燃料剩余问题,采用BP神经网络逼近算法,推导建立了一种适用于耗尽关机条件下,对导弹2级飞行进行能量管理的姿态调制方案。该方案在干扰条件下根据再入弹道倾角要求、推力偏差及射程的不同,2级点火10 s时弹上在线计算调制姿态,保证了能量消耗精度的同时为导弹在耗尽闭路导引段进行闭路制导提供了前提条件。通过仿真验证了该模型的正确性和可行性。To solve the fuel remaining issue of solid engine, an attitude angle adjustment scheme for energy management is established by using the BP neural network approximation algorithm, which is applicable to the condition of depleted shutdown. According to reentry angle, engine thrust deviation and range, the scheme computes attitude adjustment angle under interference when the second stage rocket engine ignites for 10 s, which ensures the accuracy of the energy consumption and provides a precondition for close-loop guidance. The validity and feasibility of the model are demonstrated by simulation.

关 键 词：兵器科学与技术 耗尽关机 BP神经网络 能量管理 闭路制导 

分 类 号：V412.1[航空宇航科学与技术—航空宇航推进理论与工程]