In this paper, Fault Detection and diagnosis (FDD) of faults with independent effect on system outputs by using the adaptive observer technique are investigated. At first, a class of linear systems without model uncertainty is considered. Then, a general situation where the system is subjected to either model errors or external disturbance is discussed. Robust adaptive control techniques are applied to guarantee convergence of certain signals to residual sets. An extension to FDD for a class of non-linear systems with non-linear fault function is extensively investigated. The novelty of this paper is that the strict positive realness (SPR) requirement on the plant transfer function in existing results is removed at the expense of requiring the existence of a positive definite solution to a certain matrix inequality. Furthermore, the problems of stabilization and robust stabilization by fault-tolerant control (FTC) and robust FTC are studied respectively, and faulttolerant controllers are designed to stabilize the close-loop systems. An aircraft example and a numerical example are included to verify the applicability of the proposed diagnosis methods.
An adaptive technique for robust diagnosis of faults with independent effects on system outputs
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.