2,644 research outputs found

    Feedback Control Solutions to Network Level User-equilibrium Real-time Dynamic Traffic Assignment Problems

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    A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting

    Self-Evaluation Applied Mathematics 2003-2008 University of Twente

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    This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

    Data analytics for stochastic control and prognostics in cyber-physical systems

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    In this dissertation, several novel cyber fault diagnosis and prognosis and defense methodologies for cyber-physical systems have been proposed. First, a novel routing scheme for wireless mesh network is proposed. An effective capacity estimation for P2P and E2E path is designed to guarantee the vital transmission safety. This scheme can ensure a high quality of service (QoS) under imperfect network condition, even cyber attacks. Then, the imperfection, uncertainties, and dynamics in the cyberspace are considered both in system model and controller design. A PDF identifier is proposed to capture the time-varying delays and its distribution. With the modification of traditional stochastic optimal control using PDF of delays, the assumption of full knowledge of network imperfection in priori is relaxed. This proposed controller is considered a novel resilience control strategy for cyber fault diagnosis and prognosis. After that, we turn to the development of a general framework for cyber fault diagnosis and prognosis schemes for CPSs wherein the cyberspace performance affect the physical system and vice versa. A novel cyber fault diagnosis scheme is proposed. It is capable of detecting cyber fault by monitoring the probability of delays. Also, the isolation of cyber and physical system fault is achieved with cooperating with the traditional observer based physical system fault detection. Next, a novel cyber fault prognosis scheme, which can detect and estimate cyber fault and its negative effects on system performance ahead of time, is proposed. Moreover, soft and hard cyber faults are isolated depending on whether potential threats on system stability is predicted. Finally, one-class SVM is employed to classify healthy and erroneous delays. Then, another cyber fault prognosis based on OCSVM is proposed --Abstract, page iv

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig
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