一类离散事件系统的监控器综合

前向无同步前向无冲突网是每个变迁有且只有一个输入库所并且每个库所最多有一个输入变迁的受限Petri网.针对不可控影响子网为前向无同步前向无冲突网的广义互斥约束,显式地给出了最大允许控制策略的计算方法.并用一个例子给予了说明.     

A control synthesis approach for time discrete event systems

In this paper, we introduce a control synthesis method for discrete event systems whose behavior is dependent on explicit values of time. Our goal is to control the occurrence dates of the controllable events so that the functioning of the system respects given specifications. The system to be controlled is modeled by a time Petri net. In a previous work we proposed a systematic method to build the timed automaton which models the exact behavior of a time Petri net. Furthermore, the forbidden behaviors of the system are modeled by forbidden timed automaton locations. This paper focuses on the control synthesis method, which consists in computing new firing conditions for the timed automaton transitions so that the forbidden locations are no longer reachable.     

Supervisory control of fuzzy discrete event systems: a formal approach.

Fuzzy discrete event systems (DESs) were proposed recently by Lin and Ying [19], which may better cope with the real-world problems of fuzziness, impreciseness, and subjectivity such as those in biomedicine. As a continuation of [19], in this paper, we further develop fuzzy DESs by dealing with supervisory control of fuzzy DESs. More specifically: 1) we reformulate the parallel composition of crisp DESs, and then define the parallel composition of fuzzy DESs that is equivalent to that in [19]. Max-product and max-min automata for modeling fuzzy DESs are considered, 2) we deal with a number of fundamental problems regarding supervisory control of fuzzy DESs, particularly demonstrate controllability theorem and nonblocking controllability theorem of fuzzy DESs, and thus, present the conditions for the existence of supervisors in fuzzy DESs; 3) we analyze the complexity for presenting a uniform criterion to test the fuzzy controllability condition of fuzzy DESs modeled by max-product automata; in particular, we present in detail a general computing method for checking whether or not the fuzzy controllability condition holds, if max-min automata are used to model fuzzy DESs, and by means of this method we can search for all possible fuzzy states reachable from initial fuzzy state in max-min automata. Also, we introduce the fuzzy n-controllability condition for some practical problems, and 4) a number of examples serving to illustrate the applications of the derived results and methods are described; some basic properties related to supervisory control of fuzzy DESs are investigated. To conclude, some related issues are raised for further consideration.     

Control synthesis of timed discrete event systems based onpredicate invariance

In this paper, arc-timed Petri nets are used to model controlled real-time discrete event systems, and the control synthesis problem that designs a controller for a system to satisfy its given closed-loop behavior specification is addressed. For the problem with the closed-loop behavior specified by a state predicate, real-time control-invariant predicates are introduced, and a fixpoint algorithm to compute the unique extremal control-invariant subpredicate of a given predicate, key to the control synthesis, is presented. For the problem with the behavior specified by a labeled arc-timed Petri net, it is shown that the control synthesis problem can be transformed into one that synthesizes a controller for an induced arc-timed Petri net with a state predicate specification. The problem can then be solved by using the fixpoint algorithm as well. The algorithm involves conjunction and disjunction operations of polyhedral sets and can be algorithmically implemented, making automatic synthesis of controllers for real-time discrete event systems possible.     

离散事件系统N步稳定性分析

讨论基于自动机/形式语言模型的离散事件系统(DES)稳定性问题,引入了确定性离散事件系统N步稳定性定义,并得到了稳定性的判据定理,推导了具体的算法实现。该算法具有多项式复杂度。     

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.     

Diagnosability of discrete event systems for temporary failures

Failure Detection and Diagnosis (FDD) using Discrete Event System (DES) framework is used for wide range of applications because of simplicity of both the model and associated algorithms. Initial research was focussed on permanent failures. Many systems exhibit temporary failures in the sense that system recovers to normal condition after failure. Contant et al. extended the event based DES framework, developed for permanent failure by Sampath et al. to handle temporary failures. Zad et al. developed a state based DES framework for permanent failures which has several advantages compared to the event based approach. In this paper, we extend the state based DES framework, developed for permanent failures, to handle temporary failures, maintaining the same order of complexity. The proposed DES framework has several advantages compared to that by Contant et al. namely, capability to detect failures that occur before starting execution of the diagnoser, same diagnoser for both temporary and permanent failures, etc.     

Detectability of networked discrete event systems

Detectability of discrete event systems, defined as the ability to determine the current and subsequent states, is very important in diagnosis, control, and many other applications. So far only detectability of non-networked discrete event systems has been defined and investigated. Non-networked discrete event systems assume that all the communications are reliable and instantaneous without any delays or losses. This assumption is often violated in networked systems. In this paper, we study detectability for networked discrete event systems. We investigate the impact of communication delays and losses on detectability. We define two classes of detectabilities: network detectability for determining the state of a networked discrete event systems and network D-detectability for distinguishing certain pairs of states of the systems. Necessary and sufficient conditions for network detectability and network D-detectability are derived. Methods to check network detectability and network D-detectability are also developed. Examples are given to illustrate the results.     

Diagnosability of fair discrete event systems

Failure diagnosability has been widely studied using discrete event system (DES) models. It is, however, shown in this work by means of a counterexample that the diagnosability condition, which has been shown to be necessary and sufficient in the DES context, fails to hold for many real‐world hybrid systems. This is because the abstraction employed in formulating the DES models obliterates the continuous dynamics. In the present work, a new failure diagnosability mechanism has been developed for discrete time hybrid system (DTHS) models to alleviate this problem. A new diagnosability condition is proposed and its necessity and sufficiency with respect to the diagnosability definition are established formally. Finally, the method of A‐diagnosability, which can also be used to circumvent this problem and which needs additional probabilistic information for diagnosability analysis, has been shown to have a higher computational complexity than the DTHS model based method proposed in this paper. Further, it is also highlighted that the DTHS model based diagnosability analysis technique is capable of diagnosing faults that degrade the temporal performance of the system, which cannot be handled by the A‐diagnosability analysis mechanism. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Supervisor synthesis for discrete event systems under partial observation and arbitrary forbidden state specifications

In this paper, we consider the forbidden state problem in discrete event systems modeled by partially observed and partially controlled Petri nets. Assuming that the reverse net of the uncontrollable subnet of the Petri net is structurally bounded, we compute a set of weakly forbidden markings from which forbidden markings can be reached by firing a sequence of uncontrollable/unobservable transitions. We then use reduced consistent markings to represent the set of consistent markings for Petri nets with structurally bounded unobservable subnets. We determine the control policy by checking if the firing of a certain controllable transition will lead to a subsequent reduced consistent marking that belongs to the set of weakly forbidden markings; if so, we disable the corresponding controllable transition. This approach is shown to be minimally restrictive in the sense that it only disables behavior that can potentially lead to a forbidden marking. The setting in this paper generalizes previous work by studying supervisory control for partially observed and partially controlled Petri nets with a general labeling function and a finite number of arbitrary forbidden states. In contrast, most previous work focuses on either labeling functions that assign a unique label to each observable transition or forbidden states that are represented using linear inequalities. More importantly, we demonstrate that, in general, the separation between observation and control (as considered in previous work) may not hold in our setting.     

Observability of discrete event dynamic systems

A finite state automaton is adopted as a model for discrete event dynamic systems (DEDS). Observations are assumed to be a subset of the event alphabet. Observability is defined as having perfect knowledge of the current state at points in time separated by bounded numbers of transitions. A polynomial test for observability is given. It is shown that an observer may be constructed and implemented in polynomial time and space. A bound on the cardinality of the observer state space is also presented. A notion of resiliency is defined for observers, and a test for resilient observability and a procedure for the construction of a resilient observer are presented     

The predictability of discrete event systems

Perturbation analysis and the automaton and language model are approaches developed recently for the study of discrete-event systems (DESs). The prediction of a trajectory of a new system is the essential idea of perturbation analysis. The automaton theory models a trajectory of a DES by a string in a particular language. The author formulates the trajectory prediction as a projection of a string onto a language. A sufficient condition is found for one language to be predictable from another language. Examples are given to show the application of this concept     

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 unified frame work for discrete event systems

Early fault detection and isolation minimize cost and processing time of industrial systems. The main purpose of this paper is to introduce a novel delta-marking idea to design a generalized interpreted Petri net-based fault detection and isolation scheme (IPN-based diagnoser) for all PN models. This idea overcomes the event detectability problem that restricts the performance of the conventional dignosers to certain types of Petri net model. Furthermore, a unified framework for a discrete event system that comprises a PN-based model, a PN-based supervisor, and a PN-based diagnoser of a process under consideration, is built in this paper. In addition, this paper addresses some issues for industrial systems modeling and supervision. A rapid thermal process (RTP) is used as an industrial process to test the proposed unified framework after revising its PN-model. This scheme is not only developed for RTPs, but also can be employed for industrial processes with certain modifications depending on the nature of their structures. Simulation results have confirmed the effectiveness of the proposed unified framework.     

An optimal effective controller for discrete event systems

An approach to the online synthesis of an optimal effective controller for discrete event systems is presented. The optimal effective controller can achieve the prescribed (cumulative) effectiveness measure while minimizing the total cost incurred for the execution of events. This approach is constructed over a generalized control framework for automata‐based discrete event systems, which allows event enforcement in addition to the (original) event disablement/enablement as the control mechanism. The optimal effective control policy generated by this approach is proved to be the least restrictive among all the possible optimal effective control policies for the given online expansion tree of the system behavior. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

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.     

Finitely recursive process models for discrete event systems

A class of discrete-event models called finitely recursive processes (FRP) is introduced. These models are motivated by problems in supervisory control, while some of the formal structure is based on C.A.R. Hoare's (1985) communicating sequential processes. Although only preliminary work is presented, it is believed that for many problems it offers a formalism that is superior to that of finite-state machines recently introduced in control theory. Simple examples illustrate the calculus of operators for FRPs. A more complex exercise is worked out to show how the formalism is used to construct a scheme for handling connections in a data network. This preliminary work needs to be extended in several directions, especially in directions that can assist implementation of real controllers based on the FRP formalism. Some specific suggestions towards this end are made