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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Georgios Zogopoulos-Papaliakos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens Greece Dept. of Computer Science and Telecommunications University of Thessaly Greece

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

Fault-tolerant control is currently the most important step towards increased autonomy for Unmanned Aerial Vehicles (UAVs). In this work, we consider actuator and airframe faults in fixed-wing UAVs and show that an online Flight Envelope (FE) calculation can interpret their effect on the achievable trim trajectories. Subsequently, we design a fully integrated control scheme with a RRT-based planner and 3 Nonlinear Model Predictive control (MPC) layers. The FE is provided at each control layer with the beneficial result that non-trimmable, unstable trajectories are avoided. Results from high-fidelity simulations are provided.

关键词： Iron Aircraft Atmospheric modeling Trajectory Aerospace control Numerical models Aerodynamics

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Modified indexing algorithm based on priority queue in metric space for MVP tree 4

Modified indexing algorithm based on priority queue in metri...

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4th International Conference on Future Networks and Distributed systems, ICFNDS 2020

作者： Fomin, Vladimir Aleksandrov, Igor Gallyamov, Denis Kirichek, Ruslan Dept. of Information Systems Herzen State Pedagogical University of Russia Saint Petersburg Russia Dept. of Software Engineering and Computer Science Bonch-Bruevich Saint Petersburg State University of Telecommunications Saint Petersburg Russia Bonch-Bruevich Saint Petersburg State University of Telecommunications Saint Petersburg Russia V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781450388863

The Internet of Things (IoT) algorithms process huge amounts of heterogeneous data in real-time. One of the most computationally intensive tasks using cloud technologies is the task of clustering and classifying data. The authors propose to develop an approach to data classification within the "Query by Similarity"paradigm, which uses the technology of data indexing based on Metric Access Methods (MAM). To improve the performance of data indexing, this paper proposes a similar nearest neighbor search method combining a multiple vantage point tree (MVP) and improved algorithms for processing the priority queue of nodes. The following two algorithms for processing the priority queue of nodes were developed: 1) algorithm for all kinds of points-queries, which makes it possible to take into account parent nodes of all higher levels;2) algorithm for grouped based on clustering of points-queries by reusing previously obtained search results. Experimental results confirm the effectiveness of the proposed approaches and algorithms. © 2020 ACM.

关键词： Nearest neighbor search

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Modelling and real-time optimisation of a heat-exchanger network ⁎

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IFAC-PapersOnLine 2020年第2期53卷 11780-11785页

作者： María P. Marcos José Luis Pitarch César de Prada Systems Engineering and Automatic Control Dept. EII Universidad de Valladolid. C/Real de Burgos s/n 47011 Valladolid Spain Institute of Sustainable Processes C/Real de Burgos s/n 47011 Valladolid Spain

This work proposes a hybrid mathematical model and an optimisation-based tool to support the management of a heat-recovery section (formed by several heat exchangers) in a fibre-production factory. The purpose of the network is to heat different products using several hot sources, employed as utilities. Furthermore, concerns about the degradation of the equipment due to fouling are explicitly taken into account. Hence, the goals are to allocate the hot sources to heat exchangers and to suggest which heat exchanger should be cleaned to achieve optimal economic operation. Experimental models for the overall heat-transfer coefficients with respect to the flows have been identified, and production constraints are considered too. The problem is formulated such that it can be solved in a real-time optimisation fashion via mixed-integer non-linear programming. The approach has been tested through plant historical situations.

关键词： RTO pulp industry heat exchangers fouling MINLP decision support

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Learning Requirements for Stealth Attacks 44

Learning Requirements for Stealth Attacks

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44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019

作者： Sun, Ke Esnaola, Inaki Tulino, Antonia M. Vincent Poor, H. Dept. of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Nokia Bell Labs HolmdelNJ07733 United States

ISBN: (纸本)9781479981311

The learning data requirements are analyzed for the construction of stealth attacks in state estimation. In particular, the training data set is used to compute a sample covariance matrix that results in a random matrix with a Wishart distribution. The ergodic attack performance is defined as the average attack performance obtained by taking the expectation with respect to the distribution of the training data set. The impact of the training data size on the ergodic attack performance is characterized by proposing an upper bound for the performance. Simulations on the IEEE 30-Bus test system show that the proposed bound is tight in practical settings. © 2019 IEEE.

关键词： Information theory

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Temporal Pixel Intensity Processing from Fluoroscopic Angiography

Temporal Pixel Intensity Processing from Fluoroscopic Angiog...

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E-Health and Bioengineering Conference (EHB)

作者： Irina-Andra Tache Dept. of Automatic Control and Systems Engineering University Politehnica of Bucharest Bucharest Romania

The fluoroscopic angiography comprises a temporal sequence of images acquired with a certain frequency. Hence the time density curves can be generated from the temporal and pixels' intensities information. In the paper is presented a new method to process these curves in order to further extract hemodynamic parameters from cardiac X-ray angiography.

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Feed-forward control for a Drinking Water Treatment Plant chlorination process

Feed-forward control for a Drinking Water Treatment Plant ch...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： J. Gamiz H. Mart´nez A. Grau Y. Bolea R. Vilanova Automatic Control Dept. Universitat Politecnica de Catalunya UPC Barcelona Dept. de Sistemas de Control Industrial de Aguas de Barcelona Aigües de Barcelona Barcelona Department of Electronic Engineering Universitat Politecnica de Catalunya UPC Barcelona Department of Telecommunications and Systems Engineering Universitat Autonoma de Barcelona Barcelona

ISBN: (数字)9781728189567

ISBN: (纸本)9781728189574

Chlorination in drinking water treatment plants (DWTP) is the final process applied to water before it is sent to storage tanks in the supply network for subsequent human consumption. An excessive dosage of chlorine or, conversely, too small a dosage, may breach existing legal regulations on mandatory limits. In DWTP where there is no significant variability in the quality of the water to be treated, a type of control that is proportional to the flow rate in the effluent can have fully satisfactory results. Therefore, Proportional-Integral (PI) control is a rather frequently used solution. However, when there are inherently long delays in the process, variability in the quality of the water to be treated and considerable variations alternative type is needed. This article presents the strategy and results of a control method that proposes a Fuzzy based feed-forward system to complement an existing PI control. The control system results are shown as applied to the DWTP of Barcelona city, producing satisfactory experimental results.

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Information Theoretic Data Injection Attacks with Sparsity Constraints

arXiv

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arXiv 2020年

作者： Ye, Xiuzhen Esnaola, Iñaki Perlaza, Samir M. Harrison, Robert F. Dept. of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Dept. of Electrical Engineering Princeton University PrincetonNJ08544 United States INRIA Centre de Recherche de Sophia Antipolis - Méditerranée France

Information theoretic sparse attacks that minimize simultaneously the information obtained by the operator and the probability of detection are studied in a Bayesian state estimation setting. The attack construction is formulated as an optimization problem that aims to minimize the mutual information between the state variables and the observations while guaranteeing the stealth of the attack. Stealth is described in terms of the Kullback-Leibler (KL) divergence between the distributions of the observations under attack and without attack. To overcome the difficulty posed by the combinatorial nature of a sparse attack construction, the attack case in which only one sensor is compromised is analytically solved first. The insight generated in this case is then used to propose a greedy algorithm that constructs random sparse attacks. The performance of the proposed attack is evaluated in the IEEE 30 Bus Test Case. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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Text Mining of Medical Records

Text Mining of Medical Records

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E-Health and Bioengineering Conference (EHB)

作者： Irina Andra Tache Monica Dragoicea Elena-Simona Apostol Ciprian-Octavian Truica Dept. of Automatic Control and Systems Engineering University Politehnica of Bucharest Bucharest Romania Computer Science and Engineering Department University Politehnica of Bucharest Bucharest Romania

The patients with cardiovascular diseases undergo complex medical procedures, including medical imaging, blood biochemistry analysis, physical examination, etc. The digitization of information is an intensive process in e-health therefore, in this paper there are presented some methods to extract important data from medical records of patients suffering from coronary artery diseases organized in PDF files.

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Universal Privacy Guarantees for Smart Meters

Universal Privacy Guarantees for Smart Meters

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IEEE International Symposium on Information Theory

作者： Miguel Arrieta Iñaki Esnaola Michelle Effros Dept. of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Dept. of Electrical Engineering California Institute of Technology Pasadena CA USA

Smart meters enable improvements in electricity distribution system efficiency at some cost in customer privacy. Users with home batteries can mitigate this privacy loss by applying charging policies that mask their underlying energy use. A battery charging policy is proposed and shown to provide universal privacy guarantees subject to a constraint on energy cost. The guarantee bounds our strategy's maximal information leakage from the user to the utility provider under general stochastic models of user energy consumption. The policy construction adapts coding strategies for non-probabilistic permuting channels to this privacy problem.

关键词： Batteries Privacy Energy consumption Measurement Mutual information Silicon Random processes

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Comprehensive review of models and methods for inferences in bio-chemical reaction networks

arXiv

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arXiv 2019年

作者： Loskot, Pavel Atitey, Komlan Mihaylova, Lyudmila College of Engineering Swansea University Swansea United Kingdom Dept. of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

Key processes in biological and chemical systems are described by networks of chemical reactions. From molecular biology to biotechnology applications, computational models of reaction networks are used extensively to elucidate their non-linear dynamics. Model dynamics are crucially dependent on parameter values which are often estimated from observations. Over past decade, the interest in parameter and state estimation in models of (bio-) chemical reaction networks (BRNs) grew considerably. Statistical inference problems are also encountered in many other tasks including model calibration, discrimination, identifiability and checking as well as optimum experiment design, sensitivity analysis, bifurcation analysis and other. The aim of this review paper is to explore developments of past decade to understand what BRN models are commonly used in literature, and for what inference tasks and inference methods. Initial collection of about 700 publications excluding books in computational biology and chemistry were screened to select over 260 research papers and 20 graduate theses concerning estimation problems in BRNs. The paper selection was performed as text mining using scripts to automate search for relevant keywords and terms. The outcome are tables revealing the level of interest in different inference tasks and methods for given models in literature as well as recent trends. In addition, a brief survey of general estimation strategies is provided to facilitate understanding of estimation methods which are used for BRNs. Our findings indicate that many combinations of models, tasks and methods are still relatively sparse representing new research opportunities to explore those that have not been considered - perhaps for a good reason. The most common models of BRNs in literature involve differential equations, Markov processes, mass action kinetics and state space representations whereas the most common tasks in cited papers are parameter inference and model ident

关键词： Surveys

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