Three-dimensional midcourse guidance using neural networks for interception of ballistic targets

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A suboptimal midcourse guidance law is obtained for interception of free-fall targets in the three-dimensional (3D) space. Neural networks are used to approximate the optimal feedback strategy suitable for real-time implementation. The fact that the optimal trajectory in the 3D space does not deviate much from a vertical plane justifies the use of the two-dimensional (2D) neural network method previously studied. To regulate the lateral errors in the missile motion produced by the prediction error of the intercept point, the method of feedback linearization is employed. Computer simulations confirm the superiority of the proposed scheme over linear quadratic regulator (LQR) guidance and proportional navigation (PN) guidance as well as its approximating capability of the optimal trajectory in the 3D space.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2002-04
Language
English
Article Type
Article
Keywords

TO-AIR MISSILES; ROBUST; LAW

Citation

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, v.38, no.2, pp.404 - 414

ISSN
0018-9251
URI
http://hdl.handle.net/10203/79230
Appears in Collection
AE-Journal Papers(저널논문)
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