Predictability of event occurrences in partially-observed discrete-event systems

This paper studies the problem of predicting occurrences of a significant event in a partially-observed discrete-event system. The predictability of occurrences of an event in a system is defined in the context of formal languages. The predictability of a language is a stronger condition than the diagnosability of the language. Two necessary and sufficient conditions for predictability of occurrences of an event in systems modeled by regular languages are presented. Both conditions can be algorithmically tested. The first condition employs diagnosers. The second condition employs verifiers and results in a polynomial-time (in the number of states) complexity test for verification of predictability. When predictability holds, diagnosers can be used online to predict the significant event.     

Reliable supervisory control for general architecture of decentralized discrete event systems

In this paper, we investigate the reliable decentralized supervisory control of discrete event systems (DESs) under the general architecture, where the decision for controllable events is a combination of the conjunctive and disjunctive fusion rules. By reliable control, we mean that the performance of closed-loop systems will not be degraded even in the face of possible failures of some local supervisors. The main contributions are twofold. First, a necessary and sufficient condition for the existence of a k-reliable decentralized supervisor under the general architecture is presented after introducing notions of -controllability and k-reliable -coobservability. Second, a polynomial-time algorithm to verify the reliable -coobservability of a specification is proposed.     

Decentralized control of networked discrete event systems with communication delays

In many practical systems, supervisory control is not performed by one centralized supervisor, but by multiple local supervisors. When communication networks are used in such a system as the medium of information transmission, the communication channels between local supervisors and the system to be controlled will unavoidably result in communication delays. This paper investigates how to use these local supervisors to control the system in order to satisfy given specifications even under communication delays. The specifications are described by two languages: a minimal required language which specifies the minimal required performance that the supervised system must have and a maximal admissible language which specifies the maximal boundary that the supervised system must be in. The results show that if the control problem is solvable, then there exists the minimal control policy which can be calculated based on state estimates. Furthermore, we derive algorithms to check whether the control problem is solvable or not.     

The concept of residuals for fault localization in discrete event systems

In this paper an approach for fault localization in closed-loop Discrete Event Systems is proposed. The presented diagnosis method allows fault localization using a fault-free system model to describe the expected system behavior. Via a systematic comparison of the observed and the expected behavior, a fault can be detected and a set of fault candidates is determined. Inspired by residuals known from diagnosis in continuous systems, different set operations are introduced to generate the fault candidate set. After fault detection and a first fault localization, a procedure is given to render the fault localization more precisely by an analysis of the further observed system behavior. Special emphasis is given to the use of identified models for the fault-free system behavior. The approach is explained using a laboratory manufacturing facility.     

Delay-coobservability and its algebraic properties for the decentralized supervisory control of discrete event systems with communication delays

In networked control systems, uncontrollable events may unexpectedly occur at a plant before a proper control command is applied to it due to communication delays. In this paper, we address the problem of decentralized supervisory control under such communication delays based on the C&P (conjunctive and permissive) and D&A (disjunctive and antipermissive) decision architecture. In particular, for the existence of a decentralized supervisor, we present the notion of delay-coobservability of a given language specification and a polynomial-time algorithm for verifying it. In addition, algebraic properties of the delay-coobservability are investigated. We further present a synthesis method of the decentralized supervisor for practical usefulness.     

Decentralized supervisory control of discrete event systems with communication delays based on conjunctive and permissive decision structures

In many practical discrete event systems (DESs), some unexpected and uncontrollable events can subsequently occur before a proper control action is actually applied to a plant due to communication delays. For such DESs, this paper investigates necessary and sufficient conditions for the existence of a nonblocking decentralized supervisor that can correctly achieve a given language specification when the decentralized supervisor is assumed to have a conjunctive and permissive decision structure. In particular, this paper presents a notion of delay-coobservability for a given language specification and shows that it is a key condition for the existence of such a decentralized supervisor.     

Active fault tolerant control of discrete event systems using online diagnostics

The 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.     

Diagnosability of fuzzy discrete event systems

In this paper, discrete event systems (DESs) are reformulated as fuzzy discrete event systems (FDESs) and fuzzy discrete event dynamical systems (FDEDSs). These frameworks include fuzzy states, events and IF-THEN rules. In these frameworks, all events occur at the same time with different membership degrees. Fuzzy states and events have been introduced to describe uncertainties that occur often in practical problems, such as fault diagnosis applications. To measure a diagnoser’s fault discrimination ability, a fuzzy diagnosability degree is proposed. If the diagnosability of the degree of the system yields one a diagnoser can be implemented to identify all possible fault types related to a system. For any degree less than one, researchers should not devote their time to distinguish all possible fault types correctly. Thus, two different diagnosability definitions FDEDS and FDES are introduced. Due to the specialized fuzzy rule-base embedded in the FDEDS, it is capable of representing a class of non-linear dynamic system. Computationally speaking, the framework of diagnosability of the FDEDS is structurally similar to the framework of diagnosability of a non-linear system. The crisp DES diagnosability has been turned into the term fuzzy diagnosability for the FDES. The newly proposed diagnosability definition allows us to define a degree of diagnosability in a class of non-linear systems. In addition, a simple fuzzy diagnosability checking method is introduced and some numerical examples are provided to illustrate this theoretical development. Finally, the potential applications of the proposed method are discussed.     

A template-based data specification framework for modeling physical security systems

Simulation studies often fail to provide any useful result due to its success being highly dependent on the skills of the analyst to understand a system and then correctly identify all the required data parameters and dependent variables. This paper describes a template-based framework to help identify and specify the components and data parameters for developing models of physical security systems. The layered framework consists of 15 templates built on top of 14 data primitives representing 119 data parameters. The modeling framework has been programmed as an internet-based web application and is simulation language-independent. The usefulness of the framework was tested and shown to have a significant impact on improving the identification of system components and their associated data parameters.     

Formal approach to fault diagnosis in distributed discrete event systems with OBDD

In this paper, we study the fault diagnosis problem for distributed discrete event systems. The model assumes that the system is composed of distributed components which are modeled in labeled Petri nets and interact with each other via sets of common resources (places). Further, a component’s own access to a common resource is an observable event. Based on the diagnoser approach proposed by Sampath et al., a distributed fault diagnosis algorithm with communication is presented. The distributed algorithm assumes that the local diagnosis process can exchange messages upon the occurrence of observable events. We prove the distributed diagnosis algorithm is correct in the sense that it recovers the same diagnostic information as the centralized diagnosis algorithm. Furthermore, we introduce the ordered binary decision diagrams (OBDD) in order to manage the state explosion problem in state estimation of the system.     

A modified normality condition for decentralized supervisory control of discrete event systems

In this paper, we study nonblocking decentralized supervisory control of discrete event systems. We introduce a modified normality condition defined in terms of a modified natural projection map. The modified normality condition is weaker than the original one and stronger than the co-observability condition. Moreover, it is preserved under union. Given a marked language specification, there exists a nonblocking decentralized supervisor for the supremal sublanguage which satisfies L_m(G)-closure, controllability, and modified normality. Such a decentralized supervisor is more permissive than the one which achieves the supremal L_m(G)-closed, controllable, and normal sublanguage.     

Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

Abstraction-based verification of codiagnosability for discrete event systems

In this paper, we investigate the verification of codiagnosability for discrete event systems (DES). That is, it is desired to ascertain if the occurrence of system faults can be detected based on the information of multiple local sites that partially observe the overall DES. As an improvement of existing codiagnosability tests that resort to the original DES with a potentially computationally infeasible state space, we propose a method that employs an abstracted system model on a smaller state space for the codiagnosability verification. Furthermore, we show that this abstraction can be computed without explicitly evaluating the state space of the original model in the practical case where the DES is composed of multiple subsystems.     

New nonlinear residual feedback observer for fault diagnosis in nonlinear systems

The increased complexity of plants and the development of sophisticated control systems have necessitated the parallel development of efficient Fault Detection and Isolation (FDI) systems. This paper discusses a model based technique, viz., observers for detecting and isolating parametric and sensor faults. In this paper, a novel diagonal nonlinear residual feedback observer is proposed which is valid for a certain class of nonlinear systems where, subject to other conditions, the state depends nonlinearly on the fault. A number of typical chemical engineering systems can be represented by models of this form. The structure of the observer ensures that the residuals are diagonally affected by the faults. Conditions for exact decoupling of residuals are presented and convergence of the observer in the presence of step faults is proved using Lyapunov like analysis. Multiple observers and a decision logic module are used for FDI when there are un-monitored faults. Results are presented from numerical simulations of an illustrative example and a typical chemical engineering system: a counter-current heat exchanger.     

On-line fault detection in discrete event systems by Petri nets and integer linear programming

The paper addresses the fault detection problem for discrete event systems in a Petri Net (PN) framework. Assuming that the structure of the PN model and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions associated with the system legal behaviour and that the marking reached after the firing of any transition is unknown. The proposed diagnoser works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. The results characterize the properties that the PN modelling the system fault behaviour has to fulfill in order to reduce the on-line computational effort.     

Optimal sensor activation for diagnosing discrete event systems

The problem of dynamic sensor activation for event diagnosis in partially observed discrete event systems is considered. Diagnostic agents are able to activate sensors dynamically during the evolution of the system. Sensor activation policies for diagnostic agents are functions that determine which sensors are to be activated after the occurrence of a trace of events. The sensor activation policy must satisfy the property of diagnosability of centralized systems or codiagnosability of decentralized systems. A policy is said to be minimal if there is no other policy, with strictly less sensor activation, that achieves diagnosability or codiagnosability. To compute minimal policies, we propose language partition methods that lead to efficient computational algorithms. Specifically, we define “window-based” language partitions for scalable algorithms to compute minimal policies. By refining partitions, one is able to refine the solution space over which minimal solutions are computed at the expense of more computation. Thus a compromise can be achieved between fineness of solution and complexity of computation.     

Decentralized failure diagnosis of discrete event systems

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.     

Decentralized supervisory control of nondeterministic discrete event systems: The existence condition of a robust and nonblocking supervisor

This paper addresses a decentralized supervisory control problem for an uncertain discrete event system (DES) modeled by a set of possible nondeterministic automata with unidentified internal events. For a given language specification, we present the existence condition of a robust and nonblocking decentralized supervisor that achieves this specification for any nondeterministic model in the set. In particular, we show that the given language specification can be achieved based on the properties of its controllability and coobservability with respect to the overall nominal behavior of the uncertain DES. It is further shown that the existence of a nonblocking decentralized supervisor can be examined with a trajectory model of the language specification.     

Lagrange stability and boundedness of discrete event systems

Recently it has been shown that the conventional notions of stability in the sense of Lyapunov and asymptotic stability can be used to characterize the stability properties of a class of logical discrete event systems (DES). Moreover, it has been shown that stability analysis via the choice of appropriate Lyapunov functions can be used for DES and can be applied to several DES applications including manufacturing systems and computer networks (Passino et al. 1994, Burgess and Passino 1994). In this paper we extend the conventional notions and analysis of uniform boundedness, uniform ultimate boundedness, practical stability, finite time stability, and Lagrange stability so that they apply to the class of logical DES that can be defined on a metric space. Within this stability-theoretic framework we show that the standard Petri net-theoretic notions of boundedness are special cases of Lagrange stability and uniform boundedness. In addition we show that the Petri ent-theoretic approach to boundedness analysis is actually a Lyapunov approach in that the net-theoretic analysis actually produces an appropriate Lyapunov function. Moreover, via the Lyapunov approach we provide a sufficient condition for the uniform ultimate boundedness of General Petri nets. To illustrate the Petri net results, we study the boundedness properties of a rate synchronization network for manufacturing systems. In addition, we provide a detailed analysis of the Lagrange stability of a single-machine manufacturing system that uses a priority-based part servicing policy.