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Simulation of Two-Rate Neural Network Control for Stochastic Model of an Experimental AircraftIgor ASTROV, Sergei TATARLY, Svetlana TATARLY |
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Author keywords
Aircraft control, models, multi-rate, neural networks, simulation
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About this article
Date of Publication: 2006-04-02
Volume 6, Issue 1, Year 2006, On page(s): 75 - 83
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: Not assigned
Abstract
The nature of the multi-rate dynamics of the process makes it very attractive for applications, since the multi-rate phenomena are complex. This paper presents a research methodology for describing a two-rate stochastic control system as a state-space (SS) type decomposed models of multi-input/multi-output (MIMO) stochastic subsystems with the /fast/ and /slow/ neural networks (NNs) control structures. An illustrative example from the aircraft industry - decomposed two-rate NN control of stochastic model of a tracking system for an experimental aircraft - was carried out using the proposed two-rate SS decomposition technique. The results of decomposition of an original stochastic system on two-rate autonomous subsystems are tested with the help of the block diagrams of functioning for the given original control system with single linear-quadratic-Gaussian controller (LQGC) and for the two-rate control system with six neural network reference controllers (NNRCs). This example demonstrates that this research technique results in simplified low-order MIMO autonomous subsystems with various discretization periods and with various speeds of actuation, and shows the quality of the proposed technique. The simulation results with use of software package Simulink demonstrate that this research technique would work for real-time MIMO stochastic systems. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
