DocumentCode
359042
Title
Identification of subsonic jet by dynamical recursive neural network and validation by Lyapunov exponents
Author
Djamaï, L. ; Coirault, P. ; Mehdi, D.
Author_Institution
Lab. d´´Autom. et d´´Inf. Ind., Ecole Superieure d´´Ingenieurs de Poiters, France
Volume
3
fYear
2000
fDate
2000
Firstpage
1710
Abstract
The goal of this article is to identify a subsonic jet model generated in an industrial wind tunnel (blower) from actual measurements of the speed. For that, a new phase space is constructed by delay method (MOD). This construction enables one to extract invariants from the system. The identification based on a dynamical recursive neural network uses the time series of measurement. The validation of the model is achieved if the invariants resulting from the real system and those resulting from the model are nearly identical
Keywords
Lyapunov methods; jets; neural nets; phase space methods; recursive estimation; subsonic flow; time series; Lyapunov exponent validation; MOD; blower; delay method; dynamical recursive neural network; industrial wind tunnel; measurement time series; model validation; phase space; subsonic jet identification; Chaos; Delay effects; Fluid flow measurement; Jacobian matrices; Neural networks; Phase measurement; Robustness; Solid modeling; Time measurement; Velocity measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2000. Proceedings of the 2000
Conference_Location
Chicago, IL
ISSN
0743-1619
Print_ISBN
0-7803-5519-9
Type
conf
DOI
10.1109/ACC.2000.879493
Filename
879493
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