Meera Sampath

Diagnosability of discrete-event systems

Fault detection and isolation is a crucial and challenging task in the automatic control of large complex systems. We propose a discrete-event system (DES) approach to the problem of failure diagnosis. We introduce two related notions of diagnosability of DESs in the framework of formal languages and compare diagnosability with the related notions of observability and invertibility. We present a systematic procedure for detection and isolation of failure events using diagnosers and provide necessary and sufficient conditions for a language to be diagnosable. The diagnoser performs diagnostics using online observations of the system behavior; it is also used to state and verify off-line the necessary and sufficient conditions for diagnosability. These conditions are stated on the diagnoser or variations thereof. The approach to failure diagnosis presented in this paper is applicable to systems that fall naturally in the class of DESs; moreover, for the purpose of diagnosis, most continuous variable dynamic systems can be viewed as DESs at a higher level of abstraction. >

Failure diagnosis using discrete-event models

Detection and isolation of failures in large, complex systems is a crucial and challenging task. The increasingly stringent requirements on performance and reliability of complex technological systems have necessitated the development of sophisticated and systematic methods for the timely and accurate diagnosis of system failures. We propose a discrete-event systems (DES) approach to the failure diagnosis problem. This approach is applicable to systems that fall naturally in the class of DES; moreover, for the purpose of diagnosis, continuous-variable dynamic systems can often be viewed as DES at a higher level of abstraction. We present a methodology for modeling physical systems in a DES framework and illustrate this method with examples. We discuss the notion of diagnosability, the construction procedure of the diagnoser, and necessary and sufficient conditions for diagnosability. Finally, we illustrate our approach using realistic models of two different heating, ventilation, and air conditioning (HVAC) systems, one diagnosable and the other not diagnosable. While the modeling methodology presented here has been developed for the purpose of failure diagnosis, its scope is not restricted to this problem; it can also be used to develop DES models for other purposes such as control.

Failure diagnosis using discrete event models

We propose a discrete event systems (DES) approach to the failure diagnosis problem. We present a methodology for modeling physical systems in a DES framework. We discuss the notion of diagnosability and present the construction procedure of the diagnoser. Finally, we illustrate our approach using a heating, ventilation and air conditioning (HVAC) system.<<ETX>>

Failure diagnosis of dynamic systems: an approach based on discrete event systems

We present the salient features of a methodology for failure diagnosis of dynamic systems that can be modeled as discrete event systems. This methodology was introduced by Sampath et al. for centralized systems and subsequently extended by Debouk et al. (2000) for certain classes of decentralized systems. We discuss how to perform detection and identification of unobservable fault events using diagnosers, which are finite-state automata that are built from the discrete-event model of the system under consideration. Examples of diagnosers are given. Comparisons with other methodologies for diagnosing dynamic systems are given.

A decentralized scheme for real-time optimization of traffic signals

A real time, highly decentralized, adaptive traffic signal optimization method, ALLONS-D, based on the rolling horizon dynamic programming technique, is presented. We describe the basic architecture, the system model, and the optimization scheme of ALLONS-D. We compare ALLONS-D with other approaches to signal control via several sets of simulation results. The margins of improvement are significant when compared with the standard Websters criteria for signal setting. The feasibility of on-line implementation of ALLONS-D is discussed as well as on-going evaluations and extensions.

A hybrid approach to failure diagnosis of industrial systems

This paper presents a hybrid approach to failure diagnosis that integrates the qualitative discrete event systems diagnostic methodology with quantitative analysis based techniques. The primary motivation for this hybrid approach is to achieve failure diagnosis in systems with limited sensor availability. The proposed scheme combines the relative advantages of the quantitative and the qualitative diagnostic schemes, and it allows integration of a variety of diagnostic technologies in one unified framework. The approach is illustrated using the paper feeder system of a digital copier as an example.

AN OPERATIONAL APPROACH TO BUDGET-CONSTRAINED RELIABILITY ALLOCATION

Abstract In this paper the problem of maximal increase of system reliability is formulated as a resource allocation problem under a budget constraint. Dynamic programing is used for the optimal solution. Time to system failure is dictated by a Markov process. The system is composed of several subsystems. Each subsystem has several possible configurations that exhibit different levels of fault tolerance and incur different incremental costs at different times. Configuration dependence among subsystems is allowed. An example resembling a fault tolerant industrial process is presented, for which the proposed algorithm is used to obtain a set of maximally reliable solutions corresponding to a set of budget constraints.

Combining Qualitative & Quantitative Reasoning - A Hybrid Approach to Failure Diagnosis of Industrial Systems

Abstract This paper presents a hybrid approach to failure diagnosis of industrial systems. The proposed diagnostic system integrates the qualitative discrete event systems diagnostic methodology with quantitative analysis based techniques. The primary motivation for this hybrid approach is to achieve failure diagnosis in systems with limited sensor availability. The proposed scheme has the following key advantages: (i) it integrates a variety of diagnostic technologies in one unified framework; (ii) it combines the relative advantages of the quantitative and the qualitative diagnostic schemes; and (iii) it provides the ability to study the diagnosability properties of the resulting hybrid system using existing theory of diagnosis developed for discrete event systems. The proposed approach is illustrated using the paper feeder system of a digital copier as an example.