323,446 research outputs found
Safe diagnosability for fault-tolerant supervision of discrete-event systems
No full textThe problem of achieving fault-tolerant supervision of discrete-event systems is considered from the viewpoint of safe and timely diagnosis of unobservable faults. To this end, the new property of safe diagnosability is introduced and studied. Standard definitions of diagnosability of discrete-event systems deal with the problem of detecting the occurrence of unobservable fault events using model-based inferencing from observed sequences of events. In safe diagnosability, it is required in addition that fault detection occur prior to the execution of a given set of forbidden strings in the failed mode of operation of the system. For instance, this constraint could be required to prevent local faults from developing into failures that could cause safety hazards. If the system is safe diagnosable, reconfiguration actions could be forced upon the detection of faults prior to the execution of unsafe behaviour, thus achieving the objective of fault-tolerant supervision. Necessary and sufficient conditions for safe diagnosability are derived. In addition, the problem of explicitly considering safe diagnosability in controller design, termed active safe diagnosis problem, is formulated and solved. A brief discussion of safe diagnosability for timed models of discrete-event systems is also provided
Diagnosability Analysis of a Class of Hierarchical State Machines
No full textThis paper addresses the problem of fault detection and isolation for a particular class of discrete event dynamical systems called hierarchical finite state machines (HFSMs). A new version of the property of diagnosability for discrete event systems tailored to HFSMs is introduced. This notion, called L1-diagnosability, captures the possibility of detecting an unobservable fault event using only high level observations of the behavior of an HFSM. Algorithms for testing L1-diagnosability are presented. In addition, new methodologies are presented for studying the diagnosability properties of HFSMs that are not L1-diagnosable. These methodologies avoid the complete expansion of an HFSM into its corresponding flat automaton by focusing the expansion on problematic indeterminate cycles only in the associated extended diagnoser
On the diagnosability of a class of hierarchical state machines
No full textThis paper addresses the problem of Fault Detection and Isolation for a particular class of discrete event dynamic systems named Hierarchical Finite State Machines (HFSMs). A new version of the property of diagnosability for discrete event systems tailored to HFSMs is introduced. This notion, called L1-diagnosability, captures the possibility of detecting an unobservable fault event using only high level observations of HFSMs. Algorithms for testing L1- diagnosability are presented. In addition, guidelines are presented for studying the diagnosability of HFSMs that are not L1-diagnosable
Optimal sensor selection for ensuring diagnosability in labeled bounded Petri nets
No full textThis paper studies the problem of optimal static sensor selection for ensuring diagnosability in labeled
bounded and unbounded Petri nets. Starting from a non-diagnosable labeled Petri net system, we present
a systematic procedure to design a new labeling function that makes the system diagnosable and
optimizes a given objective function. This procedure employs a particular net, called Verifier Net, that
is built from the original Petri net and provides necessary and sufficient conditions for diagnosability.
We exploit the system structure captured in the verifier net to guide the search for the desired new
labeling function. The search is performed over an unfolding of the reachability/coverability tree of the
verifier net and follows a set of rules that capture the relabeling strategy. We allow for unobservable
transitions that cannot be labeled as well as for multiple fault classes. We formulate an integer linear
programming problem that finds an optimal labeling function when numerical costs are associated with
transition relabeling
Divergence Properties of Labeled Petri Nets and Their Relevance for Diagnosability Analysis
No full textIn this note, we focus on labeled Petri nets and formalize two properties, language divergence and marking divergence, discussing their relevance for diagnosability analysis. In particular, we review the results for diagnosability and K-diagnosability presented in an article entitled 'A new approach for diagnosability analysis of Petri nets using verifier nets' that we coauthored. We show that these results apply to nets that are language divergence-free, an assumption that was not explicitly mentioned in that article. In addition, we also provide an alternative structural assumption - which does not require testing the behavioral property of divergence-freeness - under which the above results hold
Active fault tolerant control of discrete event systems using online diagnostics
No full textThe aim of this paper is to deal with the problem of fault tolerant control in the framework of discrete event systems modeled as automata. A fault tolerant controller is a controller able to satisfy control specifications both in nominal operation and after the occurrence of a fault. This task is solved by means of a parameterized controller that is suitably updated on the basis of the information provided by online diagnostics: the supervisor actively reacts to the detection of a malfunctioning component in order to eventually meet degraded control specifications. Starting from an appropriate model of the system, we recall the notion of safe diagnosability as a necessary step in order to achieve fault tolerant control. We then introduce two new notions: (i) “safe controllability”, which represents the capability, after the occurrence of a fault, of steering the system away from forbidden zones and (ii) “active fault tolerant system”, which is the property of safely continuing operation after faults. Finally, we show how the problem can be solved using a general control architecture based on the use of special kind of diagnoser, called “diagnosing controller”, which is used to safely detect faults and to switch between the nominal control policy and a bank of reconfigured control policies. A simple example is used to illustrate the new notions and the control architecture introduced in the paper
A fault tolerant architecture for supervisory control of discrete event systems
No full textIn this paper the problem of Fault Tolerant Control (FTC) in the framework of Discrete Event Systems (DES) modeled as automata is considered. The approach we follow is the so-called active approach in which the supervisor actively reacts to the detection of a malfunctioning component in order to eventually meet degraded control specifications. Starting from an appropriate model of the system, we recall the notion of safe diagnosability as a necessary step in order to achieve fault tolerant supervision of DES. We then introduce two new notions: (i) "safe controllability", which represents the capability, after the occurrence of a fault, of steering the system away from forbidden zones and (ii) "active fault tolerant system", which is the property of safely continuing operation after faults. We show how it is possible to define a general control architecture to deal with the FTC problem by introducing a special
kind of automaton, called a "diagnosing-controller"
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