Adaptive Critic based Neural Network for Control-Constrained Agile Missile
Abstract
This chapter uses the adaptive critic approach, which was introduced in Chapters 3 and 4, to steer an agile missile with bounds on the angle of attack (control variable) from various initial Mach numbers to a given final Mach number in minimum time while completely reversing its flight path angle. While a typical adaptive critic consists of a critic and controller, the agile missile problem needs chunking in terms of the independent control variable and, therefore, cascades of critics and controllers. Detailed derivations of equations and conditions on the constraint boundary are provided. for numerical experiments, the authors consider vertical plane scenarios. Numerical results demonstrate some attractive features of the adaptive critic approach and show that this formulation works very well in guiding the missile to its final conditions for this state constrained optimization problem from an envelope of initial conditions.
Recommended Citation
S. N. Balakrishnan and D. Han, "Adaptive Critic based Neural Network for Control-Constrained Agile Missile," Handbook of Learning and Approximate Dynamic Programming, pp. 463 - 478, Institute of Electrical and Electronics Engineers, Jan 2004.
The definitive version is available at https://doi.org/10.1109/9780470544785.ch18
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Artificial neural networks; Dynamic programming; Equations; Function approximation; Missiles; Optimal control
International Standard Book Number (ISBN)
978-047054478-5;978-047166054-5
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2004
