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Machine Intelligence Research

Erschienen in:

01.06.2013

Sensor/Actuator Faults Detection for Networked Control Systems via Predictive Control

verfasst von: Yu-Yan Zhang, Jun-Ling Zhang, Xiao-Yuan Luo, Xin-Ping Guan

Erschienen in: Machine Intelligence Research | Ausgabe 3/2013

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Abstract

Quantized Fault detection for sensor/actuator faults of networked control systems(NCSs) with time delays both in the sensor-to-controller channel and the controller-to-actuator channel, is concerned in the paper. The fault model is set up based on the possible cases of sensor/actuator faults. Then the model predictive control is used to compensate the time delay. When the sensors and actuators are all healthy, an H? stability criteria of the state predictive observer is obtained in terms of linear matrix inequality. A new threshold computational method that conforms to the actual situations is proposed. Then the thresholds of false alarm rate(FAR) and miss detection rate(MDR) are presented by using our proposed method, which are also compared with the ones given in the existing literatures. Finally, some numerical simulations are shown to demonstrate the effectiveness of the proposed method.

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Titel: Sensor/Actuator Faults Detection for Networked Control Systems via Predictive Control
verfasst von: Yu-Yan Zhang
Jun-Ling Zhang
Xiao-Yuan Luo
Xin-Ping Guan
Publikationsdatum: 01.06.2013
Verlag: Springer-Verlag
Erschienen in: Machine Intelligence Research / Ausgabe 3/2013
Print ISSN: 2731-538X
Elektronische ISSN: 2731-5398
DOI: https://doi.org/10.1007/s11633-013-0710-4

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