基于多环QFT的高超声速飞行器鲁棒控制

阐述了定量反馈理论(QFT)的基本原理和设计方法,针对超燃冲压发动机不同工作状态时高超声速飞行器不确定性模型,应用多环QFT设计了高超声速飞行器纵向飞行控制系统;仿真结果表明,运用QFT方法设计的控制系统不仅具有良好的跟踪性能和抗干扰性能,而且能够很好地解决飞行控制系统由于模型参数具有不确定性而造成的控制系统鲁棒性设计问题,并从工程应用角度为高超飞行器纵向飞行控制系统提供了一种鲁棒控制设计方案。     

Analytical formulation to compute QFT bounds: The envelope method

This paper describes an analytical formulation to compute quantitative feedback theory (QFT) bounds in one‐degree‐of‐freedom feedback control problems. The new approach is based on envelope curves and shows that a QFT control specification can be expressed as a family of circumferences. Then, the controller bound is defined by the envelope curve of this family and can be obtained as an analytical function. This offers the possibility of studying the QFT bounds in an analytical way with several useful properties. Gridding methods are avoided, resulting in a lower computational effort procedure. The new formulation improves the accuracy of previous methods and allows the designer to calculate multivalued bounds. Copyright © 2009 John Wiley & Sons, Ltd.     

Sensor management for tracking smart targets

We consider the problem of tracking a “smart” target. That is, a target that is aware it is being tracked and modifies its behaviour accordingly. To track such targets effectively it is necessary to modify the behaviour of the tracking sensor in response to the target. We consider that the best framework for such a problem is that of a mathematical game. In this paper, we consider an idealised version of this problem that illustrates some of the issues that can occur when attempting to track a smart target and the utility of a game theoretic framework.     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

Toward a programming theory for rational agents

An important problem in agent verification is a lack of proper understanding of the relation between agent programs on the one hand and agent logics on the other. Understanding this relation would help to establish that an agent programming language is both conceptually well-founded and well-behaved, as well as yield a way to reason about agent programs by means of agent logics. As a step toward bridging this gap, we study several issues that need to be resolved in order to establish a precise mathematical relation between a modal agent logic and an agent programming language specified by means of an operational semantics. In this paper, we present an agent programming theory that provides both an agent programming language as well as a corresponding agent verification logic to verify agent programs. The theory is developed in stages to show, first, how a modal semantics can be grounded in a state-based semantics, and, second, how denotational semantics can be used to define the mathematical relation connecting the logic and agent programming language. Additionally, it is shown how to integrate declarative goals and add precompiled plans to the programming theory. In particular, we discuss the use of the concept of higher-order goals in our theory. Other issues such as a complete axiomatization and the complexity of decision procedures for the verification logic are not the focus of this paper and remain for future investigation. Part of this research was carried out while the first author was affiliated with the Nijmegen Institute for Cognition and Information, Radboud University Nijmegen.     

A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products

Manufacturing systems produce their products by making use of three main strategies: make-to-order, make-to-stock and hybrid (combination of MTO and MTS strategies) systems. Hence, several products must be considered and partitioned in terms of many different conflicting criteria, leading to a large set of subjective or ambiguous data. Thus, an effective evaluation approach is essential to improve decision quality. In this paper a comprehensive decision, making structure is proposed to choose the proper strategy for producing the products. It consists of a novel hybrid methodology, which combines analytical hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) for partitioning of products. In this study, the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore, fuzzy AHP methodology is applied to determine the weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

Estimation of distributions involving unobservable events: the case of optimal search with unknown Target Distributions

We consider the problem of estimating the parameters of a distribution when the underlying events are themselves unobservable. The aim of the exercise is to perform a task (for example, search a web-site or query a distributed database) based on a distribution involving the state of nature, except that we are not allowed to observe the various “states of nature” involved in this phenomenon. In particular, we concentrate on the task of searching for an object in a set of N locations (or bins) {C ₁, C ₂,…, C _N }, in which the probability of the object being in the location C _i is p _i , where P = [p ₁, p ₂,…, p _N ] ^T is called the Target Distribution. Also, the probability of locating the object in the bin within a specified time, given that it is in the bin, is given by a function called the Detection function, which, in its most common instantiation, is typically, specified by an exponential function. The intention is to allocate the available resources so as to maximize the probability of locating the object. The handicap, however, is that the time allowed is limited, and thus the fact that the object is not located in bin C _i within a specified time does not necessarily imply that the object is not in C _i . This problem has applications in searching large databases, distributed databases, and the world-wide web, where the location of the files sought for are unknown, and in developing various military and strategic policies. All of the research done in this area has assumed the knowledge of the {p _i }. In this paper we consider the problem of obtaining error bounds, estimating the Target Distribution, and allocating the search times when the {p _i } are unknown. To the best of our knowledge, these results are of a pioneering sort - they are the first available results in this area, and are particularly interesting because, as mentioned earlier, the events concerning the Target Distribution, in themselves, are unobservable.

The pedagogical challenges to collaborative technologies

Collaborative technologies offer a range of new ways of supporting learning by enabling learners to share and exchange both ideas and their own digital products. This paper considers how best to exploit these opportunities from the perspective of learners’ needs. New technologies invariably excite a creative explosion of new ideas for ways of doing teaching and learning, although the technologies themselves are rarely designed with teaching and learning in mind. To get the best from them for education we need to start with the requirements of education, in terms of both learners’ and teachers’ needs. The argument put forward in this paper is to use what we know about what it takes to learn, and build this into a pedagogical framework with which to challenge digital technologies to deliver a genuinely enhanced learning experience.     

Cognitive-Mathematical Approaches for Evaluating Architectural Contextual Fit

The main goal of this study is to apply a scientific quantitative approach to the investigation of contextual fit. This is approached mathematically within the framework of cognitive science and research on categorization and prototypes. Two experiments investigated two leading mathematical-cognitive approaches for explaining people’s judgment of contextual fit of a new building with an architectural/urban context: prototype approach and feature frequency approach. The basic concept is that people represent the built environment via architectural prototypes and/or frequencies of encountered architectural features. In the first experiment, a group of twelve participants performed rank order tasks on artificially created architectural patterns, for the purpose of psychological scaling. Perceptual distances among all patterns were mathematically determined. In the second experiment, three groups of architectural patterns were constructed to represent assumed architectural contexts. The prototype of each context was mathematically determined according to prototype cognitive model, and based on the distances calculated in the first experiment. Fifty-six students participated in the main experiment, in which they rank ordered a group of fifteen architectural patterns in terms of contextual fit to each of the three architectural contexts. Participants’ rank order data of the fifteen patterns were regressed on both the perceptual distances from prototypes, and numbers of features shared with each architectural context. Results indicated that both prototype and feature frequency approaches significantly accounted for important portions of participants’ judgments. However, participants tended to prefer one approach to the other according to context composition. Results have implications for both research on utilizing cognitive-mathematical models in architectural research and on urban design guidelines and control.     

Denial of service attacks and defenses in decentralized trust management

Trust management is an approach to scalable and flexible access control in decentralized systems. In trust management, a server often needs to evaluate a chain of credentials submitted by a client; this requires the server to perform multiple expensive digital signature verifications. In this paper, we study low-bandwidth Denial-of-Service (DoS) attacks that exploit the existence of trust management systems to deplete server resources. Although the threat of DoS attacks has been studied for some application-level protocols such as authentication protocols, we show that it is especially destructive for trust management systems. Exploiting the delegation feature in trust management languages, an attacker can forge a long credential chain to force a server to consume a large amount of computing resource. Using game theory as an analytic tool, we demonstrate that unprotected trust management servers will easily fall prey to a witty attacker who moves smartly. We report our empirical study of existing trust management systems, which manifests the gravity of this threat. We also propose a defense technique using credential caching, and show that it is effective in the presence of intelligent attackers. A preliminary version of this paper was presented at the Second IEEE International Conference on Security and Privacy in Communication Networks, Baltimore, MD, USA, August 2006.