A Three-dimensional Self-adaptive Region Fuzzy Guidance Law Based on RBF Neural Network
In this paper,a new three-dimensional (3D) self-adaptive region fuzzy guidance law based on radial basis function (RBF) neural network (SRFGLRBF) design method was proposed.Firstly,3D motion equations for pursuit-evasion of missile and target are given.Secondly,the proposed method was applied to decreasing the miss distance,which is mostly arisen from the fixed navigation rates of traditional proportional navigation guidance laws (TPNGLs).The line of sight (LOS) rate and the closing speed between the missile and the target are taken as inputs of the fuzzy controller.The output of the fuzzy controller is the commanded acceleration.Then a nonlinear,self-adaptive region function is introduced based on the RBF neural networks to change the region.This nonlinear function can be changed with the input variables,thus can realize dynamic change of the fuzzy variable region.Finally,two engagement scenarios were examined,and a comparison between TPNGLs and the proposed PNGLRBF was made,the simulation results show that the proposed 3D SRFGLRBF can achieve ideal miss distance than TPNGLs.
3D fuzzy logic guidance law RBF neural network miss distance maneuvering aircrafts.
Jinyong Yu Ruchuan Zhang Hongchao Zhao
Department of Control Engineering,Naval Aeronautical and Astronautical University,Yantai 264001,Chin Department of Strategic Missile Engineering,Naval Aeronautical and Astronautical University,Yantai 2
国际会议
International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)
上海
英文
2008-06-29（万方平台首次上网日期，不代表论文的发表时间）