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第三十三届中国控制会议

作者： GE Yang WANG Jingcheng LI Kang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electronics Electrical Engineering and Computer ScienceQueen’s University Belfast

ISBN: (纸本)9781479947249

This paper mainly discusses the remote tracking problem with partly quantized information and packet-dropout. Since the network exists between the remote plant and the local plant, any information transmitted between each other will experience the quantization errors and may be lost. In this situation, the controller of the local system needs to consider both the exact local information and the inaccurate remote information. A state feedback controller is adopted and the theorems to design such controller are given in terms of bilinear matrix inequalities(BMIs). Moreover, an algorithm is proposed and these BMIs are converted into a convex optimization problem. Finally, the efficiency of the proposed method is demonstrated by a simulation example.

关键词： Networked control systems,robust control,quantized,remote tracking,packet-dropout

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Robust Fault Tolerant control on Distributed Networked control systems with Quantized Outputs 33

Robust Fault Tolerant Control on Distributed Networked Contr...

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第三十三届中国控制会议

ISBN: (纸本)9781479947249

In this paper, we consider the robust fault tolerant control of the distributed networked control systems(DNCSs). In DNCSs, sub-systems are connected with each other through a communication network. Each sub-system has its own sensor, controller, actuator and quantizer. The output of each sub-system will be transmitted to all other sub-systems through the network. As a result, quantization errors and packet-dropouts cannot be avoided. We also consider the actuator faults situations, including outage, loss of effectiveness and impulse which is modeled by a Markov chain in this paper. A mode-based static output feedback controller is proposed to stable the DNCSs and to meet the robust H-inf performance. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

关键词： Distributed networked control systems,robust control,fault tolerant,quantized

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Experimental Verification of a Multi-robot Distributed control Algorithm with Containment and Group Dispersion Behaviors: the Case of Dynamic Leaders

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 54-60页

作者： Hejin Zhang Zhiyun Zhao Ziyang Meng Zongli Lin Department of Automation and Key Laboratory for System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University the Access Linnaeus Centre School of Electrical Engineering Royal Institute of Technology Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algorithm is developed to drive the multi-robot system to follow a group of dynamic leaders with containment and group dispersion behaviors. The effectiveness of the algorithm is then verified on a multi-robot control platform.

关键词： Heuristic algorithms Mobile robots Robot kinematics Trajectory Dispersion Decentralized control

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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Dynamic anti-windup design for anticipatory activation:enlargement of the domain of attraction

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Science China(Information Sciences) 2014年第1期57卷 164-177页

作者： WU XiongJun LIN Zongli Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

Traditional anti-windup compensators are designed for activation immediately at the occurrence of actuator ***,anti-windup compensators were designed for actuation either after the saturation has reached a certain level or in anticipation of its *** the case of static anti-windup compensators,it has been shown that an anti-windup compensator designed for activation in anticipation of actuator saturation would lead to better performance than those designed for immediate or delayed activation could,both in terms of transient performance and the size of the domain of *** recently,it has been shown that a dynamic anti-windup compensator designed for anticipatory activation would also result in better transient performance than those designed for immediate or delayed activation *** this paper,we design dynamic anti-windup compensators for the enlargement of the domain of *** compensators are designed respectively for immediate,delayed and anticipatory *** will show by simulation that a dynamic anti-windup compensator designed for anticipatory activation would result in a larger domain of attraction than a dynamic anti-windup compensator designed for immediate or delayed activation could.

关键词： actuator saturation anti-windup anticipatory activation domain of attraction dynamic com-pensator

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一种两自由度的压电-电磁复合能量收集器(英文)

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2014年第9期15卷 711-722页

作者： Hong-yan WANG Li-hua TANG Yuan GUO Xiao-biao SHAN Tao XIE College of Computer and Control Engineering Qiqihar University State Key Laboratory of Robotics and System Harbin Institute of Technology Department of Mechanical Engineering University of AucklandAuckland 1010 New Zealand

研究目的:对一种两自由度的压电-电磁复合能量收集器进行发电性能研究。创新要点:建立了一种两自由度压电-电磁复合能量收集器发电性能的数学模型,该数学模型可以评估两自由度压电-电磁复合能量收集器中压电元件、电磁元件以及系统总输... 详细信息

研究目的:对一种两自由度的压电-电磁复合能量收集器进行发电性能研究。创新要点:建立了一种两自由度压电-电磁复合能量收集器发电性能的数学模型,该数学模型可以评估两自由度压电-电磁复合能量收集器中压电元件、电磁元件以及系统总输出功率。研究方法:对一种两自由度的压电-电磁复合能量收集器进行数学建模,并实验验证数学模型的正确性。基于实验测试得到的系统参数值,理论研究压电元件和电磁元件的机电耦合系数对不同能量收集器发电性能的影响关系,并对几种能量收集器的发电能力进行对比分析。重要结论:对于非强耦合(弱或中间耦合)的两自由度机电转换器,复合能量收集器(压电+电磁)具有比单一能量收集器(压电或电磁)更高的发电能力。

关键词：振动复合能量收集两自由度模型压电电磁

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An adaptive predictive control strategy for RMPPT under partially shaded conditions 19

An adaptive predictive control strategy for RMPPT under part...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Ma, Chao Wu, Jing Li, Ning Li, Shaoyuan Li, Kang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom

ISBN: (纸本)9783902823625

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in I-P curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method. © IFAC.

关键词： Adaptive control systems

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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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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Dynamic fuzzy modelling for organic rankine cycle systems

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ICIC Express Letters 2014年第11期8卷 3007-3013页

作者： Zhang, Jianhua Wang, Zhuofei Li, Bo Wang, Rui Lin, Mingming State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University No. 2 Beinong Road Changping District Beijing China Shisanling Pumped Storage Power Station Changping District Beijing China School of Control and Computer Engineering North China Electric Power University No. 2 Beinong Road Changping District Beijing China

Based on recursive fuzzy c-means (FCM) algorithm, the Takagi-Sugeno model is established for Organic Rankine Cycle (ORC) based waste heat recovery systems. The premise parameters are obtained by FCM algorithm while the consequent parameters are identified by forgetting factor least-square (FFLS) algorithm. The validity of identification algorithm is tested and verified. Simulation results show that the established T-S model can characterize the dynamic characteristics of the ORC system well.

关键词： Waste heat

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