4,436 research outputs found
Diagnosability of Fuzzy Discrete Event Systems
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.Comment: 14 pages; revisions have been mad
Observability and Decentralized Control of Fuzzy Discrete Event Systems
Fuzzy discrete event systems as a generalization of (crisp) discrete event
systems have been introduced in order that it is possible to effectively
represent uncertainty, imprecision, and vagueness arising from the dynamic of
systems. A fuzzy discrete event system has been modelled by a fuzzy automaton;
its behavior is described in terms of the fuzzy language generated by the
automaton. In this paper, we are concerned with the supervisory control problem
for fuzzy discrete event systems with partial observation. Observability,
normality, and co-observability of crisp languages are extended to fuzzy
languages. It is shown that the observability, together with controllability,
of the desired fuzzy language is a necessary and sufficient condition for the
existence of a partially observable fuzzy supervisor. When a decentralized
solution is desired, it is proved that there exist local fuzzy supervisors if
and only if the fuzzy language to be synthesized is controllable and
co-observable. Moreover, the infimal controllable and observable fuzzy
superlanguage, and the supremal controllable and normal fuzzy sublanguage are
also discussed. Simple examples are provided to illustrate the theoretical
development.Comment: 14 pages, 1 figure. to be published in the IEEE Transactions on Fuzzy
System
On Fault Diagnosis of random Free-choice Petri Nets
This paper presents an on-line diagnosis algorithm for Petri nets where a priori probabilistic knowledge about the plant operation is available. We follow the method developed by Benveniste, Fabre, and Haar to assign probabilities to configurations in a net unfolding thus avoiding the need for randomizing all concurrent interleavings of transitions. We consider different settings of the diagnosis problem, including estimating the likelihood that a fault may have happened prior to the most recent observed event, the likelihood that a fault will have happened prior to the next observed event. A novel problem formulation treated in this paper considers deterministic diagnosis of faults that occurred prior to the most recent observed event, and simultaneous calculation of the likelihood that a fault will occur prior to the next observed event
Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks
Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Centralized Versus Decentralized Detection of Attacks in Stochastic Interconnected Systems
We consider a security problem for interconnected systems governed by linear,
discrete, time-invariant, stochastic dynamics, where the objective is to detect
exogenous attacks by processing the measurements at different locations. We
consider two classes of detectors, namely centralized and decentralized
detectors, which differ primarily in their knowledge of the system model. In
particular, a decentralized detector has a model of the dynamics of the
isolated subsystems, but is unaware of the interconnection signals that are
exchanged among subsystems. Instead, a centralized detector has a model of the
entire dynamical system. We characterize the performance of the two detectors
and show that, depending on the system and attack parameters, each of the
detectors can outperform the other. In particular, it may be possible for the
decentralized detector to outperform its centralized counterpart, despite
having less information about the system dynamics, and this surprising property
is due to the nature of the considered attack detection problem. To complement
our results on the detection of attacks, we propose and solve an optimization
problem to design attacks that maximally degrade the system performance while
maintaining a pre-specified degree of detectability. Finally, we validate our
findings via numerical studies on an electric power system.Comment: Submitted to IEEE Transactions on Automatic Control (TAC
A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks
Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally,
conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002
and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140
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