Distributed Monitoring of Concurrent and Asynchronous Systems*
Discrete Event Dynamic Systems
Diagnosis of Discrete Event Systems Using Decentralized Architectures
Discrete Event Dynamic Systems
Trellis Processes: A Compact Representation for Runs of Concurrent Systems
Discrete Event Dynamic Systems
Partial Order Techniques for Distributed Discrete Event Systems: Why You Cannot Avoid Using Them
Discrete Event Dynamic Systems
Diagnosability Analysis of a Class of Hierarchical State Machines
Discrete Event Dynamic Systems
On the Minimization of Communication in Networked Systems with a Central Station
Discrete Event Dynamic Systems
Robust codiagnosability of discrete event systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
Automatica (Journal of IFAC)
Active fault tolerant control of discrete event systems using online diagnostics
Automatica (Journal of IFAC)
State estimation and fault detection using petri nets
PETRI NETS'11 Proceedings of the 32nd international conference on Applications and theory of Petri Nets
Distributed unfolding of petri nets
FOSSACS'06 Proceedings of the 9th European joint conference on Foundations of Software Science and Computation Structures
Safe diagnosability for fault-tolerant supervision of discrete-event systems
Automatica (Journal of IFAC)
Robust diagnosis of discrete-event systems against permanent loss of observations
Automatica (Journal of IFAC)
| Hi-index | 0.01 |
Reliable supervisory control of engineering systems requires failure diagnosis algorithms for discrete-event systems. For large, modularly designed plants, such as communication networks, robustness considerations and limitations on the communication between local sensors lead to decentralized implementations of failure diagnosis algorithms. A trade-off has to be made between the speed of diagnosis and the cost of communication and computation. An algorithm is proposed for decentralized failure diagnosis with asymmetric communication in which Diagnoser 2 estimates also the observer state of Diagnoser 1 and sends only that subset of failure states which is relevant for the other diagnoser when this is useful for Diagnoser 1's control task of failure detection and diagnosis. This algorithm can help in suggesting practically implementable heuristic algorithms.