Volume 4, Issue 3 (Journal of Control, V.4, N.3 Fall 2010)                   JoC 2010, 4(3): 47-55 | Back to browse issues page

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Abstract:   (4501 Views)
In this paper a novel stochastic adaptive sliding mode observer is developed which is able to estimate the states of an uncertain chaotic system with model and parametric uncertainties. The type of the model uncertainty could be unknown and its upper bound is estimated by adaptive methods. The unknown parameters are estimated using a proposed adaptation law. In addition, the effects of noise are considered in the observer dynamics and then the response system is modeled via stochastic differential equations. Using stochastic calculus and stochastic Lyapunov stability, the stability in probability of the states’ error system is proved. Moreover, it is proved that the states of the proposed observer converge to the drive system states while the adaptation gains of the observer remain non-singular and bounded. Since the observer can suppress the effect of noise and uncertainties and the states’ convergence is proved, proposed observer is used in a noisy chaos synchronization system.
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Type of Article: Research paper | Subject: Special
Received: 2014/06/21 | Accepted: 2014/06/21 | Published: 2014/06/21