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
Link To Document :
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