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

Similarity-Based Supervisory Control of Discrete Event Systems

Due to the appearance of uncontrollable events in discrete event systems, one may wish to replace the behavior leading to the uncontrollability of pre-specified language by some quite similar one. To capture this similarity, we introduce metric to traditional supervisory control theory and generalize the concept of original controllability to \ld-controllability, where \ld indicates the similarity degree of two languages. A necessary and sufficient condition for a language to be \ld-controllable is provided. We then examine some properties of \ld-controllable languages and present an approach to optimizing a realization.Comment: 22 pages, 5 figure

Supervisory Control of Fuzzy Discrete Event Systems

In order to cope with situations in which a plant's dynamics are not precisely known, we consider the problem of supervisory control for a class of discrete event systems modelled by fuzzy automata. The behavior of such discrete event systems is described by fuzzy languages; the supervisors are event feedback and can disable only controllable events with any degree. The concept of discrete event system controllability is thus extended by incorporating fuzziness. In this new sense, we present a necessary and sufficient condition for a fuzzy language to be controllable. We also study the supremal controllable fuzzy sublanguage and the infimal controllable fuzzy superlanguage when a given pre-specified desired fuzzy language is uncontrollable. Our framework generalizes that of Ramadge-Wonham and reduces to Ramadge-Wonham framework when membership grades in all fuzzy languages must be either 0 or 1. The theoretical development is accompanied by illustrative numerical examples.Comment: 12 pages, 2 figure

Hog Insurance Adoption and Suppliers' Discrimination: A Bivariate Probit Model with Partial Observability

This paper explores the factors that impact insurance choices. Specially designed survey questions allow one to fully observe the demand tendency by the farmers and partially observe the supply tendency by the insurance company. A joint estimation of insurance decision by both supply and demand sides suggested that factors performing different roles in affecting insurance participation game. Farmer’s age and education have positive impact on insurance demand, but are indifference to the insurance providers. Insurance suppliers care more about farmers’ experience in the field, but this experience occasionally results in overconfidence for the farmers and hence, impedes insurance purchasing. Production scales, proxy by sow inventory, is put more weight by the farmers than the suppliers when making decisions. Production efficiency measures, which performs as incentives for farmers to purchase insurance, acts as some disadvantages in the suppliers’ point of view. While the suppliers prefer customers who use vaccine, the hog producers tend to treat vaccine as a substitute for insurance so as to prevent disease risk. The study also generates discussion on the topics such as short-run vs. long-run factor impact by comparing past insurance choices and current choices. Information on choices regarding different types of insurance (hog and breeding sow) is also discussed. Results from bivairate probit model offers deeper understanding about livestock insurance choices and further insights to improve policy design and promote participation.Livestock Insurance Choices, Bivariate Probit, Partial Observability, Agribusiness, International Development, Livestock Production/Industries, Risk and Uncertainty, C35, D13, Q12,

State-Based Control of Fuzzy Discrete Event Systems

To effectively represent possibility arising from states and dynamics of a system, fuzzy discrete event systems as a generalization of conventional discrete event systems have been introduced recently. Supervisory control theory based on event feedback has been well established for such systems. Noting that the system state description, from the viewpoint of specification, seems more convenient, we investigate the state-based control of fuzzy discrete event systems in this paper. We first present an approach to finding all fuzzy states that are reachable by controlling the system. After introducing the notion of controllability for fuzzy states, we then provide a necessary and sufficient condition for a set of fuzzy states to be controllable. We also find that event-based control and state-based control are not equivalent and further discuss the relationship between them. Finally, we examine the possibility of driving a fuzzy discrete event system under control from a given initial state to a prescribed set of fuzzy states and then keeping it there indefinitely.Comment: 14 double column pages; 4 figures; to be published in the IEEE Transactions on Systems, Man, and Cybernetics--Part B: Cybernetic

Optimal conclusive discrimination of two states can be achieved locally

This paper constructs a LOCC protocol that achieves the global optimality in conclusive discrimination of any two states with arbitrary a priori probability. This can be interpreted that there is no ``non-locality'' in the conclusive discrimination of two multipartite states.Comment: 9 pages, RevTeX, no figure. Comments, criticisms and suggestions are welcom

Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection

Multispectral pedestrian detection has received extensive attention in recent years as a promising solution to facilitate robust human target detection for around-the-clock applications (e.g. security surveillance and autonomous driving). In this paper, we demonstrate illumination information encoded in multispectral images can be utilized to significantly boost performance of pedestrian detection. A novel illumination-aware weighting mechanism is present to accurately depict illumination condition of a scene. Such illumination information is incorporated into two-stream deep convolutional neural networks to learn multispectral human-related features under different illumination conditions (daytime and nighttime). Moreover, we utilized illumination information together with multispectral data to generate more accurate semantic segmentation which are used to boost pedestrian detection accuracy. Putting all of the pieces together, we present a powerful framework for multispectral pedestrian detection based on multi-task learning of illumination-aware pedestrian detection and semantic segmentation. Our proposed method is trained end-to-end using a well-designed multi-task loss function and outperforms state-of-the-art approaches on KAIST multispectral pedestrian dataset