Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Robust Estimation and Failure Detection: A Concise Treatment
Robust Estimation and Failure Detection: A Concise Treatment
Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems
Discrete Event Dynamic Systems
WODES '02 Proceedings of the Sixth International Workshop on Discrete Event Systems (WODES'02)
Distributed Monitoring of Concurrent and Asynchronous Systems*
Discrete Event Dynamic Systems
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Diagnosis of Discrete Event Systems Using Decentralized Architectures
Discrete Event Dynamic Systems
Reliable decentralized supervisory control of discrete eventsystems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Decentralized failure diagnosis of discrete event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Diagnosability Analysis Based on Component-Supported Analytical Redundancy Relations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
The complexity of codiagnosability for discrete event and timed systems
ATVA'10 Proceedings of the 8th international conference on Automated technology for verification and analysis
Verification of robust diagnosability for partially observed discrete event systems
Automatica (Journal of IFAC)
Robust diagnosis of discrete event systems against intermittent loss of observations
Automatica (Journal of IFAC)
Robust diagnosis of discrete-event systems against permanent loss of observations
Automatica (Journal of IFAC)
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We consider robust decentralized diagnosis of discrete event systems, where the goal is to detect the occurrence of unobservable fault events using a set of local diagnosers that are themselves subject to failures. We introduce a formal notion of robust decentralized diagnosability, called robust codiagnosability, and study its properties. Two different tests of robust codiagnosability are presented; one uses diagnoser automata and the other uses verifier automata. We also revisit the problem of centralized diagnosability and study the problem of diagnosability under partial observation, where the set of observable events is reduced; in this regard, we introduce the notions of partial diagnosers and indeterminate hidden cycles, which are subsequently used in the study of robust codiagnosability.