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IEEE ELectronics Packaging Technology Conference

作者： He Yunbo Hu Yongshan Chen Xin Gao Jian Yang Zhijun Zhang Kai Chen Yun Zhang Yu Tang Hui Ao Yinhui Guangdong Provincial Key Lab. of Computer Integrated Manufacturing Systems Key Laboratory of Mechanical Equipment Manufacturing and Control Technology of Ministry of Education School of Electromechanical Engineering Guangdong University of Technology

ISBN: (纸本)9781509043705

Ultrasonic is one important factor of ultrasonic wire bonding process, which is widely used in semiconductor packaging industry. control effect of ultrasonic power determines the quality and speed of wire bonding. Based on analysis of ultrasonic frequency characteristics and current response, this paper proposes a closed-loop control method of automatic frequency tracking and output current control, to improve the effectiveness of ultrasonic power, shorten the response time, and enhance the stability of ultrasonic generation. Automatic frequency tracking is based on phase lock method. Phase difference of voltage and current signals works as the feedback of the close-loop control of frequency to realize automatic frequency tracking and ensure that the ultrasonic transducer always works at resonance point. And output current control is working at constant current mode so that the vibration amplitude of ultrasonic can be better controlled by adjusting the ultrasonic current. The experimental results show that with the frequency automatic tracking method, the ultrasonic transducer system can achieve wider frequency bands, with faster phase locking and higher tracking precision. With close loop control, real-time tracking can be realized and less rise time and less overshoot of ultrasonic current can be achieved.

关键词： Ultrasonic Power Closed-loop

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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Robust H-infinity space vector model of permanent magnet synchronous motor based on genetic algorithm

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Journal of Computational Information Systems 2014年第14期10卷 5897-5905页

作者： Zang, Huaiquan Qin, Zhe Dai, Yan Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical and Engineering Yanshan University Qinhuangdao China

A robust H-infinity controller based on genetic algorithm optimization is designed for space vector control model of permanent magnet synchronous motor to improve the speed of tracking performance. A space vector control model of the system has been formed, and a quadrature-axis current loop transfer function based on a dynamic mathematical model of motor combined with decoupling technology is established. In order to obtain a good dynamic performance, the selection of the weighting function uses genetic algorithm to optimize in the process of designing the robust H-infinity. Simulation and analysis results show that the robust controller that based on genetic algorithm effectively improves the tracking performance and robustness of the system. © 2014 by Binary Information Press

关键词： Genetic algorithms

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GO-Bayes method for system modeling and safety analysis 21

GO-Bayes method for system modeling and safety analysis

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21st International Conference on Distributed Multimedia Systems, DMS 2015

作者： Cai, Guoqiang Jia, Limin Zhen, Hui Zheng, Mingming Feng, Shuai Zhou, MengChu State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)1891706381

Safety analysis ensuring the normal operation of an engineering system is important. The existing safety analysis methods are limited to relatively simple fact description and statistical induction level. Besides, many of them enjoy poor generality, and fail to achieve comprehensive safety evaluation given a system structure and collected information. This work describes a new safety analysis method, called a GO-Bayes algorithm. It combines structural modeling of the GO method and probabilistic reasoning of the Bayes method. It can be widely used in system analysis. The work takes a metro vehicle braking system as an example to verify its usefulness and accuracy. Visual implementation by Extendsim software shows its feasibility and advantages in comparison with the Fault Tree Analysis (FTA) method.

关键词： Fault tree analysis

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A software safety assessment method based on the combination of frequency analysis method and analytic hierarchy process

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AIP Conference Proceedings 2017年第1期1839卷

作者： Kehe Wu Jiahui Wei Haifeng Zhang Yingzhe Huo 1School of Control and Computer Engineering North China Electric Power University Beijing 102206 China 2State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing 100192 China 3Beijing Engineering Research Center of High-reliability IC with Power Industrial Grade Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing 100192 China 4State Grid Liaoning Information and Communication Company Shenyang 110016 China

The aim of software safety assessment is to evaluate whether the software meets the safety requirements, and this measurement is very important to ensure and confirm the software safety. This paper presents a new software safety assessment method that is based on the combination of frequency analysis and Analytic Hierarchy Process. First, use frequency analysis method to select some appropriate assessment indicators; then use the Analytic Hierarchy Process to construct the assessment system and assign suitable weight values to indicators at all layers of system; finally rate the software safety. Through the example analysis, it is proved that this method can evaluate software safety very well.

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Distributed edge control for multi-agent based on binocular vision system

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Journal of Computational Information Systems 2014年第7期10卷 2907-2915页

作者： Shao, Nuan Li, Huiguang Zou, Liying Liu, Le Key Lab. of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

For multiple Lagrange systems, the objective of distributed edge control problem is to drive all the followers converge to the edge of the convex hull spanned by the leaders. In this approach, we choose binocular vision system as sensing devices. Firstly, a pseudo-stereo visual model is proposed based on the concept of depth information sensitivity which can be used to provide the generalized coordinates of the leaders for all followers in the image coordinate system. Then, based on this new model, a distributed adaptive control algorithm is designed to compensate for the parametric uncertainties under a directed graph. Finally, the proposed control algorithm is applied to the multi-manipulators grasping control, simulation examples are provided to show the effectiveness of the controller. © 2014 Binary Information Press.

关键词： Multi agent systems

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Modeling parameter interactions in ranking SVM 15

Modeling parameter interactions in ranking SVM

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24th ACM International Conference on Information and Knowledge Management, CIKM 2015

作者： Zhang, Yaogong Xu, Jun Lan, Yanyan Guo, Jiafeng Xie, Maoqiang Huang, Yalou Cheng, Xueqi College of Computer and Control Engineering Nankai University China CAS Key Lab. of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China College of Software Nankai University China

ISBN: (纸本)9781450337946

Ranking SVM, which formalizes the problem of learning a ranking model as that of learning a binary SVM on preference pairs of documents, is a state-of-the-art ranking model in information retrieval. The dual form solution of Ranking SVM model can be written as a linear combination of the preference pairs, i.e., w = Σ(i,j)αij(xi - xj), where αij denotes the Lagrange parameters associated with each pair (i,j). It is obvious that there exist significant interactions over the document pairs because two preference pairs could share a same document as their items. Thus it is natural to ask if there also exist interactions over the model parameters αij, which we may leverage to propose better ranking model. This paper aims to answer the question. Firstly, we found that there exists a low-rank structure over the Ranking SVM model parameters αij, which indicates that the interactions do exist. Then, based on the discovery, we made a modification on the original Ranking SVM model by explicitly applying a low-rank constraint to the parameters. Specifically, each parameter αij is decomposed as a product of two low-dimensional vectors, i.e., αij = (υi,υj), where vectors vi and vj correspond to document i and j, respectively. The learning process, thus, becomes to optimize the modified dual form objective function with respect to the low-dimensional vectors. Experimental results on three LETOR datasets show that our method, referred to as Factorized Ranking SVM, can outperform state-of-the-art baselines including the conventional Ranking SVM. © 2015 ACM.

关键词： Information retrieval

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Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

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Nature biotechnology 2020年第4期38卷 504页

作者： Christian Lieven Moritz E Beber Brett G Olivier Frank T Bergmann Meric Ataman Parizad Babaei Jennifer A Bartell Lars M Blank Siddharth Chauhan Kevin Correia Christian Diener Andreas Dräger Birgitta E Ebert Janaka N Edirisinghe José P Faria Adam M Feist Georgios Fengos Ronan M T Fleming Beatriz García-Jiménez Vassily Hatzimanikatis Wout van Helvoirt Christopher S Henry Henning Hermjakob Markus J Herrgård Ali Kaafarani Hyun Uk Kim Zachary King Steffen Klamt Edda Klipp Jasper J Koehorst Matthias König Meiyappan Lakshmanan Dong-Yup Lee Sang Yup Lee Sunjae Lee Nathan E Lewis Filipe Liu Hongwu Ma Daniel Machado Radhakrishnan Mahadevan Paulo Maia Adil Mardinoglu Gregory L Medlock Jonathan M Monk Jens Nielsen Lars Keld Nielsen Juan Nogales Intawat Nookaew Bernhard O Palsson Jason A Papin Kiran R Patil Mark Poolman Nathan D Price Osbaldo Resendis-Antonio Anne Richelle Isabel Rocha Benjamín J Sánchez Peter J Schaap Rahuman S Malik Sheriff Saeed Shoaie Nikolaus Sonnenschein Bas Teusink Paulo Vilaça Jon Olav Vik Judith A H Wodke Joana C Xavier Qianqian Yuan Maksim Zakhartsev Cheng Zhang Novo Nordisk Foundation Center for Biosustainability Technical University of Denmark Lyngby Denmark. Systems Biology Lab Amsterdam Institute of Molecular and Life Sciences (AIMMS) Vrije Universiteit Amsterdam Amsterdam the Netherlands. BioQUANT/COS Heidelberg University Heidelberg Germany. Ecole Polytechnique Fédérale de Lausanne Laboratory of Computational Systems Biotechnology Lausanne Switzerland. iAMB-Institute of Applied Microbiology ABBt-Aachen Biology and Biotechnology RWTH Aachen University Aachen Germany. Department of Bioengineering University of California La Jolla CA USA. Department of Chemical Engineering and Applied Chemistry University of Toronto Toronto Ontario Canada. Human Systems Biology Laboratory Instituto Nacional de Medicina Genomica & Coordinación de la Investigación Científica-Red de Apoyo a la Investigación UNAM Mexico City Mexico. Institute for Systems Biology Seattle WA USA. Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens Institute for Biomedical Informatics (IBMI) Tübingen Germany. Department of Computer Science University of Tübingen Tübingen Germany. German Center for Infection Research (DZIF) partner site Tübingen Tübingen Germany. Australian Institute for Bioengineering and Nanotechnology The University of Queensland Brisbane Queensland Australia. Argonne National Laboratory Lemont IL USA. Analytical Biosciences Division of Systems Biomedicine and Pharmacology Leiden Academic Centre for Drug Research Leiden University Leiden the Netherlands. Department of Systems Biology Centro Nacional de Biotecnología Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid Spain. Centro de Biotecnología y Genómica de Plantas (CBGP UPM-INIA) Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Madrid Spain. Department of Animal and Aquacultural Sciences Faculty of Biosciences Norwegian University of Life Sciences Oslo Norway

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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An ADMM + Consensus Based Distributed Algorithm for Dynamic Economic Power Dispatch in Smart Grid

An ADMM + Consensus Based Distributed Algorithm for Dynamic ...

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第三十四届中国控制会议

作者： Hao Xing Zhiyun Lin Minyue Fu Department of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology College of Electrical Engineering Zhejiang University School of Electrical Engineering and Computer Science University of Newcastle

ISBN: (纸本)9781467374439

In this paper, we propose a distributed algorithm for the dynamic economic dispatch problem(DEDP) in a smart grid scenario. Different from the static economic dispatch problem(SEDP), the DEDP aims at minimizing the aggregate operating costs of a group of generators over a time period with ramp rate constraints. The proposed algorithm is based on the average consensus algorithm on undirected graphs and the alternating direction method of multipliers(ADMM). Our algorithm is distributed in the sense that no leader or master nodes are needed, while all the nodes(generators) conduct local computation and merely communicate with their neighbors. Convergence analysis shows that the proposed algorithm converges to the optimal solution.

关键词： Economic Dispatch,Dynamic Economic Dispatch,Distributed Convex Optimization,Smart Grid

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Design and analysis of an adaptive RBF neural network controller for two-eye robot visual system

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Journal of Computational Information Systems 2014年第17期10卷 7517-7527页

作者： Li, Guoyou Li, Hengrui Zhang, Boqiang Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

Aiming at solving the problem of control performance due to the inaccuracy in the two-eye robot visual servoing system modeling, an RBF neural network based on the adaptive algorithm is proposed, which is used to identify the uncertainties of the modeling. A dynamic control law is put forward for compensating the uncertainties of the modeling, an adaptive law is put forward to ensure the boundness of the neural network's weights and a kinematic control law is put forward which takes the errors between the actual position and the target position of the manipulators as input. The stability of the two control laws is demonstrated using the Lyapunov stability theorems, and the stability of the manipulator system which is under the proposed control laws is illustrated. The results, which are obtained from the Matlab simulation, verify the high performance of the control strategy.

关键词： Kinematics

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