SEPNATC Fault Detection and Isolation via a Novel Convex Optimization Scheme

This work deals with the design of nonlinear observers and their application to fault diagnosis and isolation. Themethodology is based on convex optimization techniques; it considers the general problem of unmeasurable premises.Algebraic rearrangements and Taylor series are employed in order to obta...

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Bibliographic Details
Published in:Revista IEEE América Latina 2019-07, Vol.17 (7), p.1096-1101
Main Authors: Quintana, Daniel, Estrada-Manzo, Victor, Bernal, Miguel
Format: Article
Language:English
Subjects:
Convex analysis
Convex functions
Convex Optimization
Convexity
Fault detection
Fault diagnosis
IEEE transactions
Linear matrix inequalities
Linear Matrix Inequality
Nonlinear Observer
Observers
Optimization
Optimization techniques
Silicon
System dynamics
Taylor series
Tensors
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Summary:This work deals with the design of nonlinear observers and their application to fault diagnosis and isolation. Themethodology is based on convex optimization techniques; it considers the general problem of unmeasurable premises.Algebraic rearrangements and Taylor series are employed in order to obtain an adequate error system dynamics. Thus,the error system is exactly expressed as a convex tensor-product which allows designing the observer gains by means oflinear matrix inequalities. Academic examples are provided in order to illustrate the advantages of the proposal.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2019.8931196