Crisp Discrete Event Systems Research Articles

Opacity Measures of Fuzzy Discrete Event Systems

Opacity, as an important security property, has been well investigated in crisp discrete event systems. However, in some practical systems, the general behaviors, secret and nonsecret behaviors obtained by the intruder need to be expressed as fuzzy sets rather than crisp sets. Under this situation, the intruder makes inferences by fuzzy logic rather than classic logic, thus the notions of the fuzzy opacity measures are desired to be established. First, by means of the basic laws of fuzzy logic, a general fuzzy opacity measure, as a template, is presented, in this article, for the given generalized characterizations of secret and nonsecret behaviors. Moreover, a specific measure, called as fuzzy initial-final opacity (FIFO) measure, is investigated under the assumption that the secrets and nonsecrets can be coded into the initial-final state-pairs. In addition, two variants of FIFO measure are also proposed under the assumptions that the secrets and nonsecrets are only related to the initial-states or final-states. With these fuzzy opacity measures, the system designers can evaluate the opacity degree of the systems to be designed. To show the applicability of the fuzzy opacity measures to practical systems, we finally present an illustrative example of evaluating the location privacy protection systems in location-based services by means of the fuzzy opacity measures.

Diagnosability of Fuzzy Discrete-Event Systems: A Fuzzy Approach

In order to more effectively cope with the real-world problems of vagueness, fuzzy discrete-event systems (FDESs) were proposed by Lin and Ying recently. Then we and Cao and Ying investigated the supervisory control of FDESs independently. In this paper, we are concerned with another important issue of FDESs, the failure diagnosis. More specifically: (1) we propose a ldquofuzzy diagnosabilityrdquo approach by introducing a fuzzy diagnosability function to characterize the diagnosability degree, which takes values in the interval [0,1] rather than { 0,1}; (2) based on the observability of events, we formalize the construction of the diagnosers that are used to perform fuzzy diagnosis; (3) a number of basic properties of the diagnosers are investigated. In particular, we present a necessary and sufficient condition for failure diagnosis of FDESs. Our results generalize the important consequences of the diagnosability for crisp discrete-event systems (DESs) introduced by Sampath <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">al</i> . The newly proposed approach allows us to deal with the problem of diagnosability for both crisp DESs and FDESs; (4) in addition, a method for checking the fuzzy diagnosability for FDESs is proposed. Also, some examples are provided to illustrate the application of the diagnosability of FDESs.

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.