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arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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A hierarchical urban network control with integration of demand balance and traffic signal coordination

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IFAC-PapersOnLine 2016年第3期49卷 31-36页

作者： Zhou, Zhao Lin, Shu Xi, Yugeng Li, Dewei Zhang, Jun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control Information Processing Ministry of Education of China Shanghai200240 China School of Computer and Control Engineering University of Chinese Academy of Science Beijing100049 China Joint Institute of UM-SJTU Shanghai Jiao Tong University Shanghai200240 China

This paper concerns the integration of demand balance control and traffic flow coordination control in a hierarchical framework for complex urban traffic networks. At the first level, a complex traffic network is first partitioned into several subnetworks. The traffic dynamics in each subnetwork is modeled by utilizing the concept of Macroscopic Fundamental Diagram (MFD), which relates the network-wide space-mean flow and the number of vehicles at the aggregated level. This model aims at designing a demand balance model predictive controller (MPC), which can improve the internal flow inside the subnetwork by regulating the input flows from outside. At the second level, based on a more detailed traffic flow model, the signal timings of all intersections for each subnetwork are determined by a flow coordination MPC controller, which aims at distributing the number of vehicles in each subnetwork as homogeneously as possible. The effectiveness of the proposed approach is investigated via simulation under different scenarios on a hypothetical urban traffic network, and the performance is compared with other control strategies. © 2016

关键词： Street traffic control

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration Automation

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Conceptual Model of Problem-oriented Heterogeneous Distributed Computing Environment with Multi-agent Management

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Procedia computer science 2017年 103卷 162-167页

作者： I. Bychkov G. Oparin A. Tchernykh A. Feoktistov V. Bogdanova S. Gorsky Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov str. 134 Irkutsk Post Box 292 664033 Russia CICESE Research Center Computer Science Department Carretera Ensenada-Tijuana No. 3918 Zona Playitas Codigo Postal 22860 Apdo. Postal 360 Ensenada B.C. Mexico

One of the promising approaches to the efficient management in a heterogeneous distributed computing environment is the use of multi-agent systems. When researchers want to solve tasks in such an environment, they need utilities for the description of the processing in the specific domain, and knowledge about a software-hardware infrastructure. This multi-component knowledge is used for effective decision-making. Practice and experience of multi-agent systems show that knowledge representation is non-trivial problems. We proposed an approach to the design of the conceptual model of a heterogeneous distributed computing environment based on multi-agent management. An important component of the model is algorithmic knowledge, which provides the support of planning, resources allocation and dynamic decomposition of a problem to subproblems. This knowledge is represented as a semantic network, which describe semantic relations between concepts. Unlike to Semantic Web Services and Semantic Grids, our approach provides advanced planning abilities to support parallelism and scalability. We develop specialized high-level tools for designing and using the conceptual models.

关键词： multi-agent systems knowledge representation distributed computing environment.

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Reliability & security issues for IoT-based smart business center: Architecture & Markov model 3

Reliability & security issues for IoT-based smart business c...

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3rd International Conference on Mathematics and computers in sciences and in Industry, MCSI 2016

作者： Kharchenko, Vyacheslav Kolisnyk, Maryna Piskachova, Iryna Bardis, Nikolaos Department of Computer Systems and Networks National Aerospace University KhAI Kharkiv Ukraine Department of Automation and Control in Technical Systems National Technical University KPI Kharkiv Ukraine Department of Computer Science and Control System Ukrainian State University of Railway Transport Kharkiv Ukraine Department of Mathematics and Engineering Sciences Hellenic Military Academy Athens Vari16673 Greece

ISBN: (纸本)9781509009732

One of the key subsystems from point of view of security of the complex IoT system is the smart business center (SB?) system. Some problems the design and operation of the SBC system are analyzed. When analysis of safety of the IoT system must take into account the reliability and security of the system at several levels: The level of sensors, the level of communication (communication lines, router, switch), the server level as the control device of components of the network, the level of the entire SBC subsystem. General architecture of network of the SB? is described. Reliability and security of key SB? hardwareand software manufacturers are analysed. In particular, security issue for SB? routers is considered. Shown the Markov model, which takes into account the technical conditions of typical network components of the SBC with the presence of software vulnerabilities when exposed to hacker attacks. On this model's basis it is possible to conduct further researches directed for improving the reliability operation and safety of IoT. ©2016 IEEE.

关键词： Internet of things

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Determine Q-V characteristics of grid connected wind farms for voltage control using data driven analytics approach

Determine Q-V characteristics of grid connected wind farms f...

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Annual Meeting Industrial and Commercial Power systems Technical Conference

作者： Chowdhury Andalib-Bin-Karim Xiaodong Liang Nahidul Khan Huaguang Zhang Department of Electrical and Computer Engineering Memorial University of Newfoundland St John's NL Canada New found land and Labrador Hydro System Operation & Planning Energy Control Center St John's NL Canada College of Information Science and Engineering North eastern University Shenyang Liaoning China

ISBN: (纸本)9781509057252

Due to varying and intermittent nature of wind resource, grid connected wind farms pose significant technical challenges to power grid on power quality and voltage stability. Wind farm Q-V characteristic curve at the point of interconnection (POI) can offer valuable information for voltage control actions and provide essential indication about voltage stability. Data driven analytics is a promising approach to determine characteristics of a large complex system, physical model of which is difficult to obtain. In this paper, the data driven analytics is used to determine Q-V curve of grid connected wind farms based on measurement data recorded at the POI. Different curve fitting models, such as Polynomial, Gaussian and Rational, are evaluated and best fit is determined based on different graphical and numerical evaluation metrics. A case study is conducted using field measurement data at two grid connected wind farms currently in operation in Newfoundland and Labrador, Canada. It is found that the Gaussian (degree 2) model describes the Q-V relationship most accurately for the two wind farms. The obtained functions and processed data can be used in the voltage controller design. The plotted QV curve can also be used to determine the reactive margin at the POI for voltage stability evaluation. As a generic method, the proposed approach can be employed to determine Q-V characteristic curve of any grid connected large wind farms.

关键词： Mathematical model Wind farms Voltage control Curve fitting Stability analysis Power system stability Reactive power

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A second update on mapping the human genetic architecture of COVID-19

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Nature 2023年第7977期621卷 E7-E26页

作者： Masahiro Kanai Christine Stevens Benjamin M. Neale Mark Daly Andrea Ganna Amy Trankiem Mary K. Balaconis Samuli Ripatti Lindo Nkambul Mark J. Daly Sam Bryant Matthew Solomonson Shea J. Andrews Mattia Cordioli Juha Karjalainen Juha Mehtonen Matti Pirinen Andrea Corbetta Bradley Jermy Kati Donner Katja Kivinen Aarno Palotie Mari Kaunisto Kumar Veerapen Konrad J. Karczewski Alicia R. Martin Elizabeth G. Atkinson Kristin Tsuo Nikolas Baya Rahul Gupta Raymond K. Walters Duncan S. Palmer Gopal Sarma Nathan Cheng Wenhan Lu Claire Churchhouse Jacqueline I. Goldstein Daniel King Wei Zhou Cotton Seed Hilary Finucane F. Kyle Satterstrom Gita A. Pathak Akiko Iwasaki Karolina Chwialkowska Karolina Chwiałkowska Brooke N. Wolford Hajar Fauzan Ahmad Shea Andrews Kathrin Aprile von Hohenstaufen Puoti Palwende R. Boua Guillaume Butler-Laporte Celia M. T. Greenwood Bartha M. Knoppers Mark Lathrop Carmen L. Cadilla Francesca Colombo Nicole Dueker Chloe Kirk Atanu Kumar Dutta Yasser M. El-Sherbiny Jehan J. El-Jawhari Doaa Shahin Ahmed Elzeiny Tamer A. Mansour Madonna M. Eltoukhy Attia A. S. Mohamed Sahar Esmaeeli Annika Faucon Israel Fernández Cadenas Israel Fernandez-Cadenas Laia Llucià-Carol Natalia Cullell Elena Muiño Jara Cárcel-Márquez Margherita Francescatto Laurent Francioli Lindokuhle Nkambule Jatin Arora Soumya Raychaudhuri Caroline Cusick Lude Franke Macarena Fuentes Macarena Fuentes-Guajardo David Gómez Cabrero Emi N. Harry Philip Jansen József L. Szentpéteri Réka Várnai Elżbieta Kaja Athanasios Kousathanas Dorote Pasko Mark J. Caulfield Alex Stuckey Christopher A. Odhams Susan Walker Daniel Rhodes Richard H. Scott Loukas Moutsianas Afshan Siddiq Peter Goddard Sally Donovan Tala Zainy Fiona Maleady-Crowe Linda Todd Shahla Salehi Greg Elgar Georgia Chan Prabhu Arumugam Christine Patch Augusto Rendon Tom A. Fowler Jose E. Krieger Sanjay K. Patel Audrey Lemaçon Sophie Limou Pietro Lió Eirini Marouli Charles Hinds Minttu M. Marttila Carolina Medina-Gómez Isabelle Migeotte Soumyajit Mondal Andrés Moreno-Estrada Leire Moya Tomok Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Public Health Faculty of Medicine University of Helsinki Helsinki Finland Analytic & Translational Genetics Unit Massachusetts General Hospital Boston MA USA Stanley Center for Psychiatric Research & Program in Medical and Population Genetics Cambridge UK Institute for Molecular Medicine Finland (FIMM) Univerisity of Helsinki Helsinki Finland University of California San Francisco San Francisco CA USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Department of Psychiatry School of Medicine Yale University New Haven CT USA Veteran Affairs Connecticut Healthcare System West Haven CT USA Yale University New Haven CT USA Centre for Bioinformatics and Data Analysis Medical University of Bialystok Bialystok Poland Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA Faculty of Industrial Sciences and Technology Universiti Malaysia Pahang Pahang Malaysia Icahn School of Medicine at Mount Sinai New York NY USA Genolier Innovation Network and Hub Swiss Medical Network Genolier Healthcare Campus Genolier Switzerland Immediate Independent Multidisciplinary Med & Biotech Research Association Milan Italy Clinical Research Unit of Nanor

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Towards multi-functional light-weight long-term real-time coastal ocean observation system 11

Towards multi-functional light-weight long-term real-time co...

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11th ACM International Conference on Underwater Networks and systems, WUWNet 2016

作者： Jiang, Zhenfeng Ma, Yanming Chen, Jiali Wang, Zigeng Peng, Zheng Liu, Jun Han, Guitao Smart Ocean Industry Research Institute Nantong Jiangsu226000 China Computer Science and Engineering Department University of Connecticut StorrsCT06269 United States Computer Science Deparment City College of New York NY10031 United States Computer Science and Technology Department Jilin University Changchun Jilin130012 China State Key Laboratory of Robotics Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

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Sum-Mse performance gain of DFT-based channel estimator over frequency-domain ls one in full-duplex OFDM systems with colored interference

arXiv

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arXiv 2017年

作者： Wang, Jin Shu, Feng Lu, Jinhui Yu, Hai Chen, Riqing Li, Jun Jayakody, Dushantha Nalin K. School of Electronic and Optical Engineering Nanjing University of Science and Technology 210094 China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China China Research Institute of Radiowave Propagation National Key Laboratory of Electromagnetic Environment Qingdao266107 China National Research Tomsk Polytechnic University Department of Control System Optimization Institute of Cybernetics Russia

In this paper, we make an investigation on the summean-square-error (sum-MSE) performance gain achieved by DFT-based least-square (LS) channel estimator over frequencydomain LS one in full-duplex OFDM system in the presence of colored interference and noise. The closed-form expression of the sum-MSE performance gain is given. Its simple upper and lower bounds are derived by using inequalities of matrix eigen-values. By simulation and analysis, the upper lower bound is shown to be close to the exact value of MSE gain as the ratio of the number N of total subcarriers to the cyclic prefix length L grows and the correlation factor of colored interference increases. More importantly, we also find that the MSE gain varies from one to N/L as the correlation among colored interferences decreases gradually. According to theoretical analysis, we also find the MSE gain has very simple forms in two extreme scenarios. In the first extreme case that the colored interferences over all subchannels are fully correlated, i.e., their covariance matrix is a matrix of allones, the sum-MSE gain reduces to 1. In other words, there is no performance gain. In the second extreme case that the coloredinterference covariance matrix is an identity matrix, i.e, they are mutually independent, the achievable sum-MSE performance gain is N/L. A large ratio N/L will achieve a significant sum-MSE gain. Copyright © 2017, The Authors. All rights reserved.

关键词： Covariance matrix

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Constraint Robust Model Predictive control for Jump Markov Linear systems with Additive Disturbances

Constraint Robust Model Predictive Control for Jump Markov L...

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European control Conference

作者： Jens Tonne Olaf Stursberg Volkswagen AG Baunatal (Germany) Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel (Germany)

ISBN: (纸本)9781509025923

This paper proposes an approach to robust model predictive control (MPC) for discrete-time jump Markov linear systems (JMLS) considering polytopic constraints on the inputs and states. In a first design step, state feedback controllers, that stabilize the JMLS robustly, are calculated offline by means of a semi-definite program (SDP). These controllers are designed to satisfy the constraints and keep the states within disturbance invariant sets (DIS). To reduce the conservatism of the design approach, an SDP formulation in which the controller parameterization is independent of the Lyapunov matrices is employed. The resulting Lyapunov matrices and the DIS are used to formulate quadratic constraints for the first prediction step, that ensure robustness against additive disturbances, stability, constraint satisfaction and recursive feasibility. The stabilizing properties and low computation times of the resulting quadratically constraint quadratic program (QCQP) are illustrated by simulation.

关键词： JMLS SDP MPC

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