Fault Detection and Isolation via a Novel Convex Optimization Scheme
Keywords:
Convex optimization, Fault detection, Linear matrix inequality, nonlinear observer, Taylor seriesAbstract
This work deals with the design of nonlinear observers and their application to fault diagnosis and isolation. The methodology 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 of linear matrix inequalities. Academic examples are provided in order to illustrate the advantages of the proposal.Downloads
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Published
2019-12-02
How to Cite
Quintana, D., Estrada Manzo, V., & Bernal Reza, M. Ángel. (2019). Fault Detection and Isolation via a Novel Convex Optimization Scheme. IEEE Latin America Transactions, 17(7), 1096–1101. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/524
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