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Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems
2016
IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society
Nowadays, industrial plants are calling for highperformance fault diagnosis techniques to meet stringent requirements on system availability and safety in the event of component failures. This paper deals with robust fault estimation problems for stochastic nonlinear systems subject to faults and unknown inputs relying on Takagi-Sugeno fuzzy models. Augmented approach jointly with unknown input observers for stochastic Takagi-Sugeno models is exploited here, which allows one to estimate both
doi:10.1109/iecon.2016.7793639
dblp:conf/iecon/LiuGBS16
fatcat:65aqtupifvfovhgavgqfjcunoe