New results on decentralized diagnosis of discrete-event systems (original) (raw)
Diagnosis of Discrete Event Systems Using Decentralized Architectures
Discrete Event Dynamic Systems, 2007
Decentralized diagnosis of discrete event systems has received a lot of attention to deal with distributed systems or with systems that may be too large to be diagnosed by one centralized site. This paper casts the problem of decentralized diagnosis in a new hierarchical framework. A key feature is the exploitation of different local decisions together with appropriate rules for their fusion. This includes local diagnosis decisions that can be interpreted as "conditional decisions". Under this new framework, a series of new decentralized architectures are defined and studied. The properties of their corresponding notions of decentralized diagnosability are characterized and their relationship with existing work described. Corresponding verification algorithms are also presented and on-line diagnosis strategies discussed. *
Decentralized Failure Diagnosis of Discrete Event Systems
IEEE Transactions on Systems, Man, and Cybernetics, 2006
By decentralized diagnosis we mean diagnosis using multiple diagnosers, each possessing its own set of sensors, without involving any communication among diagnosers or to any coordinators. The notion of decentralized diagnosis is formalized by introducing the notion of codiagnosability that requires that a failure be detected by one of the diagnosers within a bounded delay. Algorithms of complexity polynomial in the size of the system and the nonfault specification are provided for: 1) testing codiagnosability, 2) computing the bound in delay of diagnosis, 3) offline synthesis of individual diagnosers, and 4) online diagnosis using them. The notion of codiagnosability and the above algorithms are initially presented in a setting of a specification language (violation of which represents a fault) and are later specialized to the case where faults are modeled as the occurrences of certain events. The notion of strong codiagnosability is also introduced to capture the ability of being certain about both the failure as well as the nonfailure conditions in a system within a bounded delay.
Unconditional decentralized structure for the fault diagnosis of discrete event systems
1st IFAC Workshop on Dependable Control of Discrete Systems (2007), 2007
This paper proposes an unconditional decentralized structure to realize the fault diagnosis of Discrete Event Systems (DES), specially manufacturing systems with discrete sensors and actuators. This structure is composed on the use of a set of local diagnosers, each one of them is responsible of a specific part of the plant. These local diagnosers are based on a modular modelling of the plant in order to reduce the state explosion. Each local diagnoser uses event-based, state based and timed models to take a decision about fault's occurrences. These models are obtained using the information provided by the plant, the controller and the actuators reactivity. All local diagnosis decisions are then merged by a Boolean operator in order to obtain one global diagnosis decision. Finally, the diagnosers are polynomial-time in the cardinality of the state space of the system. This approach is illustrated using an example of manufacturing system.
Sixth International Workshop on Discrete Event Systems, 2002. Proceedings., 2002
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.
Coordinated decentralized protocols for failure diagnosis of discrete event systems
Discrete Event Dynamic Systems, 2000
We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosability, originally introduced in Sampath et al. (1995) for centralized systems, to the proposed coordinated decentralized architecture. We specify three protocols that realize the proposed architecture; each protocol is defined by the diagnostic information generated at the local sites, the communication rules used by the local sites, and the coordinator's decision rule. We analyze the diagnostic properties of each protocol. We also state and prove conditions for a language to be diagnosable under each protocol. These conditions are checkable off-line. The on-line diagnostic process is carried out using the diagnosers introduced in Sampath et al. (1995) or a slight variation of these diagnosers. The key features of the proposed protocols are: (i) they achieve, each under a set of assumptions, the same diagnostic performance as the centralized diagnoser; and (ii) they highlight the "performance vs. complexity" tradeoff that arises in coordinated decentralized architectures. The correctness of two of the protocols relies on some stringent global ordering assumptions on message reception at the coordinator's site, the relaxation of which is briefly discussed.
A Coordinated Decentralized Protocol For Failure Diagnosis Of Discrete Event Systems
We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of two local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosability, originally introduced in [1] for centralized systems, to the proposed coordinated decentralized architecture. We specify one protocol that realizes the proposed architecture. We analyze the diagnostic properties of this protocol. The key feature of the proposed protocol is that it achieves the same diagnostic performance as the centralized diagnoser. 1 Introduction Failure detection and isolation is an important task in the automatic control of large complex systems, and consequently, the problem of failure diagnosis has received considerable attention in the literature. Many schemes ranging from fault-tree and analytical redundancy methods to discrete event ...
Polynomial Time Verification of Decentralized Diagnosability of Discrete Event Systems
IEEE Transactions on Automatic Control, 2011
The first step in the diagnosis of failure occurrences in discrete event systems is the verification of the system diagnosability. Several works have addressed this problem using either diagnosers or verifiers for both centralized and decentralized architectures. In this technical note, we propose a new algorithm to verify decentralized diagnosability of discrete event systems. The proposed algorithm requires polynomial time in the number of states and events of the system and has lower computational complexity than all other methods found in the literature. In addition, it can also be applied to the centralized case.
Decentralized modular diagnosis of concurrent discrete event systems
2008 9th International Workshop on Discrete Event Systems, 2008
The problem of decentralized modular fault diagnosis of concurrent discrete event systems, that is composed of a set of component modules, is formulated and studied. In the proposed decentralized modular framework, diagnosis is performed by the local diagnosers, located at the component sites, using their own local observations. This is to ensure the scalability of the approach with respect to the number of component modules, and we require that the local diagnosers be "modularly computable", i.e., their computation should be based on the local models, and not the global models. It is also required that there are no missed-detections (every fault is detected within a bounded number of transitions) and no false-alarms (a fault detection report is issued only when a fault has occurred). We formally define the decentralized modular diagnosis problem and introduce the notion of modular diagnosability as a key property for the existence of desired decentralized modular diagnosers. We show that under this property, the complexity for constructing the local diagnosers is polynomial in the number of local modules. We present a method for testing the modular diagnosability property by reducing it to an instance of a certain codiagnosability property for which known verification techniques exist.
Diagnosability Analysis of Discrete Event Systems with Autonomous Components
European Conference on Artificial Intelligence, 2010
Diagnosability is the property of a given partially observable system model to always exhibit unambiguously a failure behavior from its only available observations in finite time after the fault occurrence, which is the basic question that underlies diagnosis taking into account its requirements at design stage. However, for the sake of simplicity, the previous works on diagnosability analysis of discrete event systems (DESs) have the same assumption that any observable event can be globally observed, which is at the price of privacy. In this paper, we first briefly describe cooperative diagnosis architecture for DESs with autonomous components, where any component can only observe its own observable events and thus keeps its internal structure private. And then a new definition of cooperative diagnosability is consequently proposed. At the same time, we present a formal framework for cooperative diagnosability checking, where global consistency of local diagnosability analysis can be achieved by analyzing communication compatibility between local twin plants without any synchronization. The formal algorithm with its discussion is provided as well. 2 PRELIMINARIES In this section, we first describe how to model DESs with autonomous components and then give some important concepts before proposing cooperative diagnosis architecture for such systems. 2.1 System model We consider a distributed DES composed of a set of autonomous components {G 1 , G 2 ,..., G n } that communicate with each other by communication events. Moreover, any component can only observe its own observable events and thus can keep its internal structure private. This kind of system is modeled by a set of FSMs with each one representing the local model of one component.