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Event-triggered fault detection for T-S fuzzy systems subject to data losses

Ziran Chen, Baoyong Zhang, Yijun Zhang, Yongmin Li, Zhengqiang Zhang

2020International Journal of Systems Science15 citationsDOI

Abstract

This work focuses on the fault detection for nonlinear networked systems. A fault detection filter is designed to detect the fault signal under the effect of disturbance. The communication channel of the networked system is supposed to be influenced by the limited bandwidth and random data losses. To deal with these, event-triggered scheme and Bernoulli process are employed to describe the problems, respectively. According to the above situation, we employ a formulated random series to describe the input of fuzzy filter. Differential mean value theorem based method is presented to handle the asynchronous membership functions. Synthetically, linear matrix inequality approach is employed to obtain the stability conditions and the filter design process. At last, we verify the performance of this method acting in the simulation example.

Topics & Concepts

Fault detection and isolationFilter (signal processing)Control theory (sociology)Computer scienceAsynchronous communicationFuzzy logicNonlinear systemBernoulli's principleProcess (computing)Fault (geology)Real-time computingAlgorithmEngineeringArtificial intelligenceTelecommunicationsAerospace engineeringControl (management)Computer visionOperating systemPhysicsGeologyQuantum mechanicsActuatorSeismologyStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationElasticity and Wave Propagation
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