Fast adaptive unknown input observer for fault and attack estimations in nonlinear systems: an enhanced LMI approach

Shivaraj Mohite, Adil Sheikh and S. R. Wagh

International Journal of Systems Science, 2025, vol. 56, issue 10, 2246-2262

Abstract: This paper deals with the problem of robust fault estimation for the Lipschitz nonlinear systems under the influence of sensor faults and actuator faults. In the proposed methodology, a descriptor system is formulated by augmenting sensor fault vectors with the states of the system. A novel fast adaptive unknown input observer (FAUIO) structure is proposed for the simultaneous estimation of both faults and states of a class of nonlinear systems. A new LMI condition is established by utilising the $ \mathcal {H}_\infty $ H∞ criterion to ensure the asymptotic convergence of the estimation error of the developed observer. This derived LMI condition is deduced by incorporating the reformulated Lipschitz property, a new variant of Young inequality, and the well-known linear parameter varying (LPV) approach. It is less conservative than the existing ones in the literature, and its effectiveness is compared with the other proposed approaches. Further, the proposed observer methodology is extended for the disturbance-affected nonlinear system for the purpose of the reconstruction of states and faults/attacks with optimal noise attenuation. Later on, both designed approaches are validated through an application of a single-link robotic arm manipulator in MATLAB Simulink.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2024.2441466 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:56:y:2025:i:10:p:2246-2262

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2024.2441466

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().