Hypersonic Vehicle Trajectory Optimization and Control

Abstract

A dual neural network structure has been developed for the study of hypersonic vehicle trajectory optimization and control. The network structure is called an 'adaptive critic'. The uniqueness and main features of this approach are that: 1) it needs no external training, 2) it allows variability of initial conditions, and 3) it can serve as feedback control. This is used to solve a 'free final time' two-point boundary value problem that maximizes the mass at the rocket burn-out while satisfying the pre-specified burnout conditions in velocity, flightpath angle, and altitude. Numerical results are presented which illustrate the potential of this method.

Department(s)

Mechanical and Aerospace Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 The Authors, All rights reserved.

Publication Date

01 Jan 1997

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