Optimal sensor activation for diagnosing discrete event systems

DOI10.1016/j.automatica.2010.04.004zbMath1194.93140OpenAlexW1982189925WikidataQ56935641 ScholiaQ56935641MaRDI QIDQ987648

Anouck R. Girard, Weilin Wang, Feng Lin, Stéphane Lafortune

Publication date: 13 August 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2010.04.004

zbMATH Keywords

supervisory controldiscrete event systemssensor activationevent diagnosis

Mathematics Subject Classification ID

Discrete event control/observation systems (93C65)

Related Items (15)

A framework for current-state opacity under dynamic information release mechanism ⋮ Computing observers from observation policies in discrete-event systems ⋮ Deterministic supervisory control with flexible upper-bounds on observation delay and control delay ⋮ Diagnosability enforcement in labeled Petri nets using supervisory control ⋮ Online minimization of sensor activation for supervisory control ⋮ Design of decentralized critical observers for networks of finite state machines: a formal method approach ⋮ Decentralized diagnosis of discrete event systems subject to permanent sensor failures ⋮ Codiagnosability and coobservability under dynamic observations: transformation and verification ⋮ I-S detectability of partially-observed discrete event systems: a novel matrix-based method ⋮ Privacy preserving minimal observability for composite transactional services ⋮ Minimal sensor activation and minimal communication in discrete-event systems ⋮ Computation of the delay bounds and synthesis of diagnosers for decentralized diagnosis with conditional decisions ⋮ Computation of minimal event bases that ensure diagnosability ⋮ A general approach for optimizing dynamic sensor activation for discrete event systems ⋮ Implementation of inference-based diagnosis: computing delay bound and ambiguity levels

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• Minimizing the cardinality of an events set for supervisors of discrete-event dynamical systems
• Active acquisition of information for diagnosis and supervisory control of discrete event systems

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