Skip to main content
Kent Academic Repository

Variable structure observer for a class of nonlinear large-scale interconnected systems with uncertainties

Mohamed, Mokhtar, Yan, Xinggang, Spurgeon, Sarah K., Mao, Zehui (2016) Variable structure observer for a class of nonlinear large-scale interconnected systems with uncertainties. In: Variable Structure Systems (VSS), 2016 14th International Workshop on. . E-ISBN 21583986. (doi:10.1109/VSS.2016.7506949) (KAR id:57530)

Abstract

In this paper, a variable structure observer design approach is proposed for a class of nonlinear, large-scale interconnected systems in the presence of unstructured uncertainty. The modern geometric approach is exploited to explore the system structure and a transformation is developed to facilitate observer design. Using the Lyapunov direct method, a robust asymptotic observer is presented which exploits the internal dynamic structure of the system as well as the structure of the uncertainties. The bounds on the uncertainties are nonlinear and are employed in the observer design to reject the effect of the uncertainties. A numerical example is presented to illustrate the approach and the simulation results show that the proposed approach is effective.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/VSS.2016.7506949
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Xinggang Yan
Date Deposited: 27 Sep 2016 09:44 UTC
Last Modified: 09 Dec 2022 02:22 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/57530 (The current URI for this page, for reference purposes)

University of Kent Author Information

Yan, Xinggang.

Creator's ORCID: https://orcid.org/0000-0003-2217-8398
CReDIT Contributor Roles:

Spurgeon, Sarah K..

Creator's ORCID:
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.