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Uncertain Chaotic System Control via Adaptive Neural Design.
- Source :
- International Journal of Bifurcation & Chaos in Applied Sciences & Engineering; May2002, Vol. 12 Issue 5, p1097, 13p
- Publication Year :
- 2002
-
Abstract
- Though chaotic behaviors are exhibited in many simple nonlinear models, physical chaotic systems are much more complex and contain many types of uncertainties. This paper presents a robust adaptive neural control scheme for a class of uncertain chaotic systems in the disturbed strict-feedback form, with both unknown nonlinearities and uncertain disturbances. To cope with the two types of uncertainties, we combine backstepping methodology with adaptive neural design and nonlinear damping techniques. A smooth singularity-free adaptive neural controller is presented, where nonlinear damping terms are used to counteract the disturbances. The differentiability problem in controlling the disturbed strict-feedback system is solved without employing norm operation, which is usually used in robust control design. The proposed controllers can be applied to a large class of uncertain chaotic systems in practical situations. Simulation studies are conducted to verify the effectiveness of the scheme. [ABSTRACT FROM AUTHOR]
- Subjects :
- CHAOS theory
ARTIFICIAL neural networks
Subjects
Details
- Language :
- English
- ISSN :
- 02181274
- Volume :
- 12
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- International Journal of Bifurcation & Chaos in Applied Sciences & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 7227384
- Full Text :
- https://doi.org/10.1142/S0218127402004930