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AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications.

, , , and . IEEE Trans. Contr. Sys. Techn., 24 (1): 293-301 (2016)

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On the issue of LQG embedded control realization in a Maglev system., , and . MED, page 1379-1384. IEEE, (2017)A model-based embedded control hardware/software co-design approach for optimized sensor selection of industrial systems., , , and . MED, page 889-894. IEEE, (2015)Processing and Communications Rate Requirements in Sensor Networks for Physical Thread Assessment., , , , , and . CRITIS, volume 8985 of Lecture Notes in Computer Science, page 31-36. Springer, (2014)AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications., , , and . IEEE Trans. Contr. Sys. Techn., 24 (1): 293-301 (2016)Sensor fault detection with low computational cost: A proposed neural network-based control scheme., and . ETFA, page 1-6. IEEE, (2012)Optimised sensor selection for control and fault tolerance: Comparison and some new results., , and . MED, page 60-65. IEEE, (2013)AI-based low computational power actuator/sensor fault detection applied on a MAGLEV suspension., , , and . MED, page 1127-1132. IEEE, (2013)Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system., , , and . Int. J. Systems Science, 43 (10): 1785-1804 (2012)