Online learning neural architectures and cross-correlation analysis for actuator failure detection and identification

DOI10.1080/00207179608921851zbMath0850.93185OpenAlexW2024056834MaRDI QIDQ4876774

Steve Naylor, M. Innocenti, Marcello Rosario Napolitano, Charles Neppach, Giovanni Silvestri, Van Casdorph

Publication date: 17 July 1996

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179608921851

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) System identification (93B30)

Related Items (1)

Testing the covariance matrix of the innovation sequence with sensor/actuator fault detection applications

Cites Work

• Unnamed Item
• A survey of design methods for failure detection in dynamic systems
• False alarm and correct detection probabilities over a time interval for restricted classes of failure detection algorithms
• A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems
• Failure detection and identification
• Approximation by superpositions of a sigmoidal function

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