Codiagnosability and coobservability under dynamic observations: transformation and verification
From MaRDI portal
Publication:900685
DOI10.1016/j.automatica.2015.08.023zbMath1327.93269OpenAlexW1761337960MaRDI QIDQ900685
Publication date: 22 December 2015
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2015.08.023
Decentralized systems (93A14) Discrete event control/observation systems (93C65) Observability (93B07)
Related Items
Initial-state detectability of stochastic discrete-event systems with probabilistic sensor failures, A general framework for diagnosis of discrete event systems subject to sensor failures, Marking diagnosability verification in labeled Petri nets, Observability and diagnosability of finite state systems: a unifying framework, Verification complexity of a class of observational properties for modular discrete events systems, Decentralized diagnosis of discrete event systems subject to permanent sensor failures, Distributed diagnosis of discrete-event systems under dynamic event observations, Codiagnosability and coobservability under dynamic observations: transformation and verification, Trajectory detectability of discrete-event systems, Codiagnosability of discrete event systems revisited: a new necessary and sufficient condition and its applications, Computation of the delay bounds and synthesis of diagnosers for decentralized diagnosis with conditional decisions, Implementation of inference-based diagnosis: computing delay bound and ambiguity levels
Uses Software
Cites Work
- Unnamed Item
- Control of discrete-event systems. Automata and Petri net perspectives
- Minimal sensor activation and minimal communication in discrete-event systems
- Event counting of partially-observed discrete-event systems with uniformly and nonuniformly bounded diagnosis delays
- Diagnosis of discrete event systems using decentralized architectures
- Codiagnosability and coobservability under dynamic observations: transformation and verification
- Optimal sensor activation for diagnosing discrete event systems
- An algorithm for calculating indistinguishable states and clusters in finite-state automata with partially observable transitions
- On observability of discrete-event systems
- Diagnosability of discrete event systems and its applications
- Robust diagnosis of discrete event systems against intermittent loss of observations
- Coordinated decentralized protocols for failure diagnosis of discrete event systems
- Undecidable problems of decentralized observation and control on regular languages
- A formal framework for the decentralised diagnosis of large scale discrete event systems and its application to telecommunication networks
- Active acquisition of information for diagnosis and supervisory control of discrete event systems
- Introduction to Discrete Event Systems
- Supervisory control of discrete-event processes with partial observations
- Think globally, act locally: decentralized supervisory control
- Maximal Solutions in Decentralized Supervisory Control
- A polynomial algorithm for testing diagnosability of discrete-event systems
- The computational complexity of decentralized discrete-event control problems
- Diagnosability of discrete-event systems
- Decentralized Control of Discrete-Event Systems When Supervisors Observe Particular Event Occurrences
- Minimization of Dynamic Sensor Activation in Discrete Event Systems for the Purpose of Control
- Fault diagnosis in discrete-event systems: Framework and model reduction
- Minimal communication in a distributed discrete-event system
- Polynomial-time verification of diagnosability of partially observed discrete-event systems
- Global and local consistencies in distributed fault diagnosis for discrete-event systems
- On Codiagnosability and Coobservability With Dynamic Observations
- Polynomial Time Verification of Decentralized Diagnosability of Discrete Event Systems
- The Complexity of Codiagnosability for Discrete Event and Timed Systems
- Control of Networked Discrete Event Systems: Dealing with Communication Delays and Losses
