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Coordinated decentralized protocols for failure diagnosis of discrete-event systems


Coordinated Decentralized Protocols for Failure Diagnosis of Discrete Event Systems
Rami Debouk, Stephane Lafortune and Demosthenis Teneketzis Department of Electrical Engineering and Computer Science The University of Michigan, Ann Arbor, MI 48109{2122, USA fridebouk,stephane,teneketg@eecs.umich.edu; www.eecs.umich.edu/umdes Abstract
approaches in the literature have been developed for systems where the information used for fault diagnosis is centralized. A notable exception is 5], where the authors present a distributed fault monitoring method, time templates. Time templates monitoring is cited to have the advantage of being easily implemented in distributed control architectures. Many systems are decentralized in nature, for instance, the majority of technological complex systems (computer and communication networks, manufacturing, process control and power systems, etc.) are informationally decentralized. In decentralized information systems there are several work stations (decision makers, controllers, diagnosers) each having access to its own local information. The stations may communicate and exchange limited information among each other. Since this information is exchanged in real-time and over channels of limited capacity, there are propagation delays, along with faults and transmission errors. Thus, the information available to each station is incomplete, delayed, and possibly erroneous. Hence, the approaches to failure diagnosis mentioned above do not apply directly to informationally decentralized systems. Consequently, it is important to develop diagnostic methodologies for informationally decentralized systems. This fact is also recognized in 5] and 6]. In this work, we investigate failure diagnosis problems in DES under decentralized information. We refer the reader to 7, 8] for a detailed description of the work. We rst restrict attention to a coordinated decentralized architecture with two local sites communicating with a coordinator. This architecture is depicted in Figure 1.
System model Site 1 Local observations Site 2 Local observations

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 1] for centralized systems, to the proposed coordinated decentralized architecture. We specify three protocols, i.e. the diagnostic information generated at the local sites, the communication rules used by the local sites, and the coordinator's decision rule, that realize the proposed architecture. We analyze the diagnostic properties of each protocol. We also state and prove necessary and su cient conditions for a language to be diagnosable under each protocol. These conditions are checkable o -line. The on-line diagnostic process is carried out using the diagnosers introduced in 1] 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 tradeo 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 brie y discussed. Failure detection and isolation is an important task in the automatic control of large complex systems. In order to guarantee a reliable system performance, the control engineer should guarantee that the system is running safely within its normal boundaries. 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 system (DES) approaches, model based reasoning and expert systems methods, have been proposed to approach this problem. For a brief description of these methods and additional references, the interested reader is referred to 2] and the introduction of 1] and the references therein. In 1, 3, 4], the authors propose a language based approach for failure diagnosis of DES. In their framework, a language is said to be diagnosable with respect to a set of observable events and a failure partition if within a nite delay, the occurrence of any failure can be detected using the history of observable events. They model the language as a deterministic nite state machine (FSM). The diagnoser, another deterministic FSM built from the system model, is at the core of the diagnostic methodology: it is used to analyze the diagnosability properties o -line, and to perform diagnostic when it observes on-line the behavior of the system. The work in 1, 3, 4] and almost all of the failure diagnosis

Extended Summary

Local diagnostics

Local diagnostics

Communication constraints Coordinator (memory and processing constraints) Failure information Failure recovery module

Figure 1: Coordinated decentralized architecture

In Figure 1, the top block represents the complete system model. Each site is composed of two modules: an observation module and a diagnostic module. The site i, i 2 f1; 2g,

locally observes the system based on its available sensing capabilities. Therefore, a projection Pi 1] is associated with site i, where Pi is de ned on a set of observable events oi (note here that o1 and o2 need not be disjoint although sites 1 and 2 may be physically apart). The union of o1 and o2 is the set of all observable events o . Site i locally processes its own observations and generates its diagnostic information. Both sites communicate some form of their diagnostic information to the coordinator. The task of the coordinator is to process, according to a prescribed decision rule, the messages received from both sites to infer occurrences of failures. If a failure is detected by the coordinator, it is broadcasted to the failure recovery module. To analyze the coordinated decentralized architecture, we extend the notion of diagnosability, introduced in 1] for centralized systems, to the coordinated decentralized architecture. The de nition of diagnosability in 1] assumes centralization of the available information; hence it is not directly applicable to coordinated decentralized systems. Moreover, the coordinated decentralized architecture in Figure 1 represents a class of realizations of the same architecture di erentiated by the choice of the communication rules and the coordinator's decision rule. Diagnosability in the case of a coordinated decentralized architecture requires that the detection of any failure should be achieved by the coordinator within a nite delay of the occurrence of that failure. We present three speci c protocols that realize the architecture under consideration. A protocol species the diagnostic information generated at each local site, the communication rules used by the local sites, and the decision rule for failure diagnosis employed by the coordinator. Since any realization of the presented coordinated decentralized architecture cannot outperform the centralized one, a desirable objective in realizing such an architecture is to aim at diagnosing all failure types that can be diagnosed by the centralized diagnoser. Therefore, the design process should determine a failure diagnosis protocol that performs as well as the centralized diagnoser would. In case this is not feasible, conditions on the system structure may be found to guarantee that the protocol diagnoses all failure types that are diagnosed by the centralized diagnoser. We present and discuss the diagnostic properties of the suggested protocols. We state and prove necessary and su cient conditions for a language to be diagnosable under these protocols and provide o -line tests to check the diagnosability property. The on-line diagnostic process is carried out by the diagnosers introduced in 1] or a slight variation of these diagnosers. The key features of the coordinated decentralized protocols presented in this paper are: rst, they perform as well as the centralized diagnoser each under a set of assumptions; and second, they highlight the performance vs. complexity tradeo that arises in coordinated decentralized architectures. The results of this work can be extended in a straightforward manner to a coordinated decentralized architecture consisting of m (m > 2) local sites. This is explained in 8]. 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 brie y discussed. This reveals some fundamental limitations of the untimed DES mathematical model that is used. This research was supported in part by NSF grant ECS9509975 and ARO grant DAAH04-96-1-0377. 1] M. Sampath, R. Sengupta, S. Lafortune, K. Sinnamohideen, and D. Teneketzis. Diagnosability of discrete-event

systems. IEEE Trans. Automat. Contr., 40(9):1555{1575, September 1995. 2] A.D. Pouliezos and G.S. Stavrakakis. Real time fault monitoring of industrial processes. Kluwer Academic Publishers, Boston, MA, 1994. 3] M. Sampath, R. Sengupta, S. Lafortune, K. Sinnamohideen, and D. Teneketzis. Failure diagnosis using discreteevent models. IEEE Trans. Contr. Syst. Tech., 4(2):105{124, March 1996. 4] M. Sampath, S. Lafortune, and D. Teneketzis. Active diagnosis of discrete-event systems. IEEE Trans. Automat. Contr., 43(7), July 1998. 5] L. Holloway and S. Chand. Time templates for discrete event fault monitoring in manufacturing systems. In Proc. 1994 American Control Conference, pages 701{706, 1994. 6] R. Boubour, C. Jard, A. Aghasaryan, E. Fabre, and A. Benveniste. Petri net approach to fault detection and diagnosis in distributed systems: application to telecommunication networks, motivations, and modelling. In Proc. 36th IEEE Conf. on Decision and Control, San Diego, CA, December 1997. 7] R. Debouk, S. Lafortune, and D. Teneketzis. A coordinated decentralized architecture for failure diagnosis of discrete-event systems. In Proc. of WODES 1998, International Workshop on Discrete Event Systems. Published by IEE, London, England, August 1998. 8] R. Debouk, S. Lafortune, and D. Teneketzis. Coordinated decentralized protocols for failure diagnosis of discreteevent systems. Technical Report CGR97-17, Department of Electrical Engineering and Computer Science, University of Michigan, September 1997. Revised May 1998.

Acknowledgements References


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