Paper Info
Title
A Three-Dimensional Self-Adaptive Region Fuzzy Guidance Law Based On Rbf Neural Networks
Abstract
In this paper, a new three-dimensional (3D) self-adaptive region fuzzy guidance law based on radial basis function (RBF) neural networks (SRFGLRBF) design method is proposed. Firstly, 3D motion equations for pursuit-evasion of missile and target are given. Secondly, the proposed method is applied to decreasing the miss distance, which is mostly 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 regarded as the inputs of the fuzzy controller. The output of the fuzzy controller is the commanded acceleration. Then, a non-linear, self-adaptive region function is introduced based on the RBF neural networks to change the region. This non-linear function can be changed with the input variables, thus it can realise dynamic change of the fuzzy variable region. Finally, two engagement scenarios are examined and a comparison between TPNGLs and the proposed PNGLRBF is made. The simulation results show that the proposed 3D SRFGLRBF can achieve ideal miss distance better than TPNGLs.
Year
DOI
Venue
2009
10.1504/IJMIC.2009.029262
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL
Keywords
Field
DocType
three-dimensional, 3D fuzzy logic guidance law, radial basis function, RBF neural network, RBFNN, miss distance, MD, manoeuvring aircrafts
Proportional navigation,Control theory,Control theory,Missile,Fuzzy logic,Control engineering,Line-of-sight,Fuzzy control system,Artificial neural network,Fuzzy number,Law,Mathematics
Journal
Volume
Issue
ISSN
8
3
1746-6172
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Ruchuan Zhang151.23
Hongchao Zhao2136.98
Jinyong Yu327723.41