Adaptive sliding mode observer for non-linear stochastic systems with uncertainties
by Feng Qiao, Ya Zhang, Quanmin Zhu, Hua Zhang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 8, No. 1, 2009

Abstract: It is presented, in this paper, a novel adaptive sliding mode observer (ASMO) for reconstructing the states of non-linear stochastic systems with structure uncertainties, parameter perturbations and external disturbances which is presented in the Ito differential equations. The proposed ASMO uses sliding mode technique to guarantee the robustness of observation, and an adaptive law is employed to update the sliding mode gain. The estimation error of the proposed observer is theoretically proved to be mean square exponentially convergent to a limited bound. Simulation study is made on computer with MatLab for reconstructing the states of Lorenz chaotic attractor disturbed with uncertainties and polluted with noises, and the simulation results verify the effectiveness of the proposed observation strategy.

Online publication date: Fri, 09-Oct-2009

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com