基于RBFNN增益调节的自适应滑模制导律  

Adaptive Sliding Mode Guidance Law Based on RBFNN Gain Regulation

作　　者：李解[1] 雷虎民[1] 王华吉[1] 朱苏北 

机构地区：[1]空军工程大学防空反导学院,西安710051

出　　处：《弹箭与制导学报》2015年第3期19-22,共4页Journal of Projectiles,Rockets,Missiles and Guidance

基　　金：航空科学基金(20130196004)资助

摘　　要：为提高末制导精度,设计了一种RBF滑模制导律。根据滑模变结构理论推导了一种基于零化视线角速率的滑模制导律,分析了目标机动与切换项增益的关系,利用RBF神经网络对切换项增益进行在线估计,最后将所设计的RBF滑模制导律与滑模制导律、比例导引律进行仿真对比。仿真结果表明所设计的制导律能实时调节切换项增益,有效拦截不同的机动目标,减小了脱靶量并提高了系统的鲁棒性。To improve accuracy of guidance system in terminal guidance phase, a RBF sliding mode guidance law was designed. A sliding mode guidance law based on zeroing line of sight rate was deduced with the theory of sliding mode variable structure control. With analysis of relationship between target maneuvering and switch gain, RBF neural networks were used for switch gain online regulation. Finally, compared with sliding mode guidance law and proportional navigation, the simulation results show that the RBF sliding mode guidance law has stronger robustness for target maneuvering and reduces target-missing effectively.

关 键 词：滑模制导律 RBF神经网络 切换增益 

分 类 号：TJ765.3[兵器科学与技术—武器系统与运用工程]