Abstract

We investigate the use of an `adaptive critic' based controller to steer an agile missile with a constraint on the angle of attack from various initial Mach numbers to a given final Mach number in minimum time while completely reversing its flightpath angle. We use neural networks with a two-network structure called `adaptive critic' to carry out the optimization process. This structure obtains an optimal controller through solving Hamiltonian equations. This approach needs no external training; each network along with the optimality equations generates the output for the other network. When the outputs are mutually consistent, the controller output is optimal. Though the networks are trained off-line, the resulting control is a feedback control

Meeting Name

1999 American Control Conference, 1999

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Hamiltonian Equations; Adaptive Critic Based Neural Networks; Angle of Attack; Control-Constrained Agile Missile Control; Feedback; Feedback Control; Flightpath Angle; Missile Control; Neurocontrollers; Optimal Control; Optimisation; Two-Network Structure

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 1999 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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