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Title: Fuzzy Fault Detection for Markov Jump Systems With Partly Accessible Hidden Information: An Event-Triggered Approach
Authors: Cheng P.
He J.
Stojanović, Vladimir
Luan X.
Issue Date: 2021
Abstract: IEEE This article addresses the design issue of fuzzy asynchronous fault detection filter (FAFDF) for a class of nonlinear Markov jump systems by an event-triggered (ET) scheme. The ET scheme can be applied to cut down the transmission times from the system to FAFDF. It is assumed that the system modes cannot be obtained synchronously by the filter, and instead, there is a detector that can measure the estimated modes of the system. The asynchronous phenomenon between the system and the filter is characterized via a hidden Markov model with partly accessible mode detection probabilities. Applying the Lyapunov function methods, sufficient conditions for the presence of FAFDF are obtained. Finally, an application of a wheeled mobile manipulator with hybrid joints is employed to clarify that the devised FAFDF can detect the faults without any incorrect alarm.
Type: article
DOI: 10.1109/TCYB.2021.3050209
ISSN: 2168-2267
SCOPUS: 2-s2.0-85100498090
Appears in Collections:Faculty of Mechanical and Civil Engineering, Kraljevo

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