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Simulation of Missile Autopilot with Two-Rate Hybrid Neural Network SystemASTROV, I., TATARLY, S., TATARLY, S.
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Control systems, guided missile, multi-rate, neural networks, simulation
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About this article
Date of Publication: 2007-04-02
Volume 7, Issue 1, Year 2007, On page(s): 18 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2007.01004
Web of Science Accession Number: 000259841200004
This paper proposes a two-rate hybrid neural network system, which consists of two artificial neural network subsystems. These neural network subsystems are used as the dynamic subsystems controllers.1 This is because such neuromorphic controllers are especially suitable to control complex systems. An illustrative example - two-rate neural network hybrid control of decomposed stochastic model of a rigid guided missile over different operating conditions - was carried out using the proposed two-rate state-space decomposition technique. This example demonstrates that this research technique results in simplified low-order autonomous control subsystems with various speeds of actuation, and shows the quality of the proposed technique. The obtained results show that the control tasks for the autonomous subsystems can be solved more qualitatively than for the original system. The simulation and animation results with use of software package Simulink demonstrate that this research technique would work for real-time stochastic systems.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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