Abstract
We present a new neural architecture which imbeds dynamic programming solutions to solve optimal target-intercept problems. They provide feedback guidance solutions, which are optimal with any initial conditions and time-to-go, for a 2D scenario. The method discussed in this study determines an optimal control law for a system by successively adapting two networks - an action and a critic network. This method determines the control law for an entire range of initial conditions; it simultaneously determines and adapts the neural networks to the optimal control policy for both linear and nonlinear systems. In addition, it is important to know that the form of control does not need to be known in order to use this method
Recommended Citation
S. N. Balakrishnan and V. Biega, "A New Neural Architecture for Homing Missile Guidance," Proceedings of the 1995 American Control Conference, Institute of Electrical and Electronics Engineers (IEEE), Jan 1995.
The definitive version is available at https://doi.org/10.1109/ACC.1995.531278
Meeting Name
1995 American Control Conference
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Dynamic Programming; Feedback; Feedback Guidance; Homing Missile Guidance; Imbeds Dynamic Programming; Missile Guidance; Neural Architecture; Neural Net Architecture; Neural Networks; Neurocontrollers; Optimal Control; Target-Interception
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1995 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1995
