No Arabic abstract
Among notions of detectability for a discrete-event system (DES), strong detectability implies that after a finite number of observations to every output/label sequence generated by the DES, the current state can be uniquely determined. This notion is strong so that by using it the current state can be easily determined. In order to keep the advantage of strong detectability and weaken its disadvantage, we can additionally take some subsequent outputs into account in order to determine the current state. Such a modified observation will make some DES that is not strongly detectable become strongly detectable in a weaker sense, which we call {it $K$-delayed strong detectability} if we observe at least $K$ outputs after the time at which the state need to be determined. In this paper, we study $K$-delayed strong detectability for DESs modeled by finite-state automata (FSAs), and give a polynomial-time verification algorithm by using a novel concurrent-composition method. Note that the algorithm applies to all FSAs. Also by the method, an upper bound for $K$ has been found, and we also obtain polynomial-time verification algorithms for $(k_1,k_2)$-detectability and $(k_1,k_2)$-D-detectability of FSAs firstly studied by [Shu and Lin, 2013]. Our algorithms run in quartic polynomial time and apply to all FSAs, are more effective than the sextic polynomial-time verification algorithms given by [Shu and Lin 2013] based on the usual assumptions of deadlock-freeness and having no unobservable reachable cycle. Finally, we obtain polynomial-time synthesis algorithms for enforcing delayed strong detectability, which are more effective than the exponential-time synthesis algorithms in the supervisory control framework in the literature.
Opacity, as an important property in information-flow security, characterizes the ability of a system to keep some secret information from an intruder. In discrete-event systems, based on a standard setting in which an intruder has the complete knowledge of the systems structure, the standa
The state inference problem and fault diagnosis/prediction problem are fundamental topics in many areas. In this paper, we consider discrete-event systems (DESs) modeled by finite-state automata (FSAs). There exist results for decentraliz
In order to more effectively cope with the real-world problems of vagueness, {it fuzzy discrete event systems} (FDESs) were proposed recently, and the supervisory control theory of FDESs was developed. In view of the importance of failure diagnosis, in this paper, we present an approach of the failure diagnosis in the framework of FDESs. More specifically: (1) We formalize the definition of diagnosability for FDESs, in which the observable set and failure set of events are {it fuzzy}, that is, each event has certain degree to be observable and unobservable, and, also, each event may possess different possibility of failure occurring. (2) Through the construction of observability-based diagnosers of FDESs, we investigate its some basic properties. In particular, we present a necessary and sufficient condition for diagnosability of FDESs. (3) Some examples serving to illuminate the applications of the diagnosability of FDESs are described. To conclude, some related issues are raised for further consideration.
We study supervisor localization for real-time discrete-event systems (DES) in the Brandin-Wonham framework of timed supervisory control. We view a real-time DES as comprised of asynchronous agents which are coupled through imposed logical and temporal specifications; the essence of supervisor localization is the decomposition of monolithic (global) control action into local control strategies for these individual agents. This study extends our previous work on supervisor localization for untimed DES, in that monolithic timed control action typically includes not only disabling action as in the untimed case, but also ``clock preempting action which enforces prescribed temporal behavior. The latter action is executed by a class of special events, called ``forcible events; accordingly, we localize monolithic preemptive action with respect to these events. We demonstrate the new features of timed supervisor localization with a manufacturing cell case study, and discuss a distributed control implementation.
Discrete event systems (DES) have been established and deeply developed in the framework of probabilistic and fuzzy computing models due to the necessity of practical applications in fuzzy and probabilistic systems. With the development of quantum computing and quantum control, a natural problem is to simulate DES by means of quantum computing models and to establish {it quantum DES} (QDES). The motivation is twofold: on the one hand, QDES have potential applications when DES are simulated and processed by quantum computers, where quantum systems are employed to simulate the evolution of states driven by discrete events, and on the other hand, QDES may have essential advantages over DES concerning state complexity for imitating some practical problems. The goal of this paper is to establish a basic framework of QDES by using {it quantum finite automata} (QFA) as the modelling formalisms, and the supervisory control theorems of QDES are established and proved. Then we present a polynomial-time algorithm to decide whether or not the controllability condition holds. In particular, we construct a number of new examples of QFA to illustrate the supervisory control of QDES and to verify the essential advantages of QDES over DES in state complexity.