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Hybrid fuzzy and robust controller applied to a DC-DC boost converter

Hybrid fuzzy and robust controller applied to a DC-DC boost ...

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作者： De Carvalho Neto, Joao T. Salazar, Andres O. De Araujo, Fabio M.U. Cavalcanti, Anderson L. De O. Department of Computing Engineering and Automation Federal University of Rio Grande Do Norte Natal/ Rio Grande do Norte Brazil

ISBN: (纸本)9781479940325

This paper purposes a hybrid control method applied to a DC-DC Boost converter in order to maintain a constant output voltage and ensure the supply of good power quality to the load. The hybrid controller consists of a fuzzy supervisor which mixes control signals of two types of controllers: robust and fuzzy. Each one of these controllers has good performance in certain operational conditions. The supervisor determines the ideal proportion of the action provided by the controllers in each operational condition. The simulations show that fuzzy and robust control signals can be mixed to provide a good power quality to the load ensuring fast transient response and zero steady-state error due to input voltage and load variations. © 2014 IEEE.

关键词： Power quality

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Shape driven kernel adaptation in Convolutional Neural Network for robust facial trait recognition

Shape driven kernel adaptation in Convolutional Neural Netwo...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Shaoxin Li Junliang Xing Zhiheng Niu Shiguang Shan Shuicheng Yan Department of Electrical and Computer Engineering National University of Singapore Singapore Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China National Laboratory of Pattern Recognition Institute of Automation CAS Beijing China

ISBN: (纸本)9781467369657

One key challenge of facial trait recognition is the large non-rigid appearance variations due to some irrelevant real world factors, such as viewpoint and expression changes. In this paper, we explore how the shape information, i.e. facial landmark positions, can be explicitly deployed into the popular Convolutional Neural Network (CNN) architecture to disentangle such irrelevant non-rigid appearance variations. First, instead of using fixed kernels, we propose a kernel adaptation method to dynamically determine the convolutional kernels according to the spatial distribution of facial landmarks, which helps learning more robust features. Second, motivated by the intuition that different local facial regions may demand different adaptation functions, we further propose a tree-structured convolutional architecture to hierarchically fuse multiple local adaptive CNN subnetworks. Comprehensive experiments on WebFace, Morph II and MultiPIE databases well validate the effectiveness of the proposed kernel adaptation method and tree-structured convolutional architecture for facial trait recognition tasks, including identity, age and gender recognition. For all the tasks, the proposed architecture consistently achieves the state-of-the-art performances.

关键词： Kernel Shape Face Face recognition Robustness Neural networks Computer architecture

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A design of intelligent route guidance system based on shortest path algorithm

A design of intelligent route guidance system based on short...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xipeng Zhang Gang Xiong Liang Xiao Fenghua Zhu Xiongguang Yang Timo R. Nyberg School of Electrical Engineering & Automation Tianjin University Tianjin China Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Tianjin Industrial Development Area Infrastructure Management Center Tianjin China Department of Industrial Engineering and Management Aalto University Aalto Finland

ISBN: (纸本)9781467384810

With the accelerated urbanization and the development of automobile industry, traffic congestion has become serious gradually for many metropolises. Thus, it is an important and extensive method in many countries to use the intelligent transportation systems (ITS) to control traffic and to induce vehicle flows so that road congestion may be mitigated and the traffic may be more efficient. As an important part of intelligent transportation, an intelligent route guidance system (IRGS) not only regulates traffic flow of every crossroads intersections to make full use of insufficient road infrastructure, but also reduces running distance and average waiting time for every driver to reach region traffic balance. This paper explores a design of IRGS and proposes a way to address the task decomposition of traffic guidance and path selection issues. Results from the simulation experiments suggest that IRGS with shortest path algorithm can achieve better network performance and increased traffic control system efficiency. The study provides theory and method guide for the development of real application system.

关键词： Vehicles Roads Sensors Artificial intelligence Real-time systems Wireless communication

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Unobtrusive Sensing Incremental Social Contexts Using Fuzzy Class Incremental Learning

Unobtrusive Sensing Incremental Social Contexts Using Fuzzy ...

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IEEE International Conference on Data Mining (ICDM)

作者： Zhenyu Chen Yiqiang Chen Xingyu Gao Shuangquan Wang Lisha Hu Chenggang Clarence Yan Nicholas D. Lane Chunyan Miao China Electric Power Research Institute Beijing China Department of Automation Tsinghua University Beijing China Beijing Key Laboratory of Mobile Computing and Pervasive Device Chinese Academy of Sciences Beijing China Bell Labs School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781467395052

By utilizing captured characteristics of surrounding contexts through widely used Bluetooth sensor, user-centric social contexts can be effectively sensed and discovered by dynamic Bluetooth information. At present, state-of-the-art approaches for building classifiers can basically recognize limited classes trained in the learning phase; however, due to the complex diversity of social contextual behavior, the built classifier seldom deals with newly appeared contexts, which results in degrading the recognition performance greatly. To address this problem, we propose, an OSELM (online sequential extreme learning machine) based class incremental learning method for continuous and unobtrusive sensing new classes of social contexts from dynamic Bluetooth data alone. We integrate fuzzy clustering technique and OSELM to discover and recognize social contextual behaviors by real-world Bluetooth sensor data. Experimental results show that our method can automatically cope with incremental classes of social contexts that appear unpredictably in the real-world. Further, our proposed method have the effective recognition capability for both original known classes and newly appeared unknown classes, respectively.

关键词： Context Bluetooth Mobile handsets Feature extraction Learning systems Data mining Sensors

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Coordination control for generic linear multi-agent systems with time delay: a semi-discretization approach

Coordination control for generic linear multi-agent systems ...

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IEEE Annual Conference on Decision and Control

作者： Jiahu Qin Jie Sheng Huijun Gao Wei Xing Zheng Department of Automation University of Science and Technology of China Hefei 230027 P. R. China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin 150001 P. R. China School of Computing Engineering and Mathematics Western Sydney University Sydney NSW 2751 Australia

ISBN: (纸本)9781479978878

This paper aims to perform the convergence analysis for a group of linear multi-agent systems with time delay and communicating over arbitrary network topology. It is proved that within the allowable delay bound, all the agents within each closed strong component reach synchronization, while all the other agents outside the closed strong components converge to the dynamic convex hull spanned by the agents in the closed strong components. The delay bound is calculated by the method of semi-discretization, which is also useful in searching for an optimal feedback control with the fastest convergence rate for a certain time delay. A simulation example is given to illustrate the validity of the obtained results.

关键词： coordinated control Network topology Agents system clock optimal feedback control Converge convex hull COMMUNICATING

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Instrumentation to detect contamination of insulating oil in motors applied to electrical submersible pump 11

Instrumentation to detect contamination of insulating oil in...

引用

11th IEEE/IAS International Conference on Industry Applications, IEEE INDUSCON 2014

作者： Salazar, Andres O. Fonsêca, Diego A. M. Martelli, André L. Fontes, Francisco De Oliveira Quintaes, Filipe Department of Computing and Automation Engineering Federal University of Rio Grande Do Norte Natal-RN Brazil Informatics Department Federal Institute of Rio Grande Do Norte Natal-RN Brazil

ISBN: (纸本)9781479955510

The purpose of this paper is to presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type electrical submersible pump (ESP). The sensor generates an alarm signal at the moment when the contamination oil is present. This signal is transmitted to the surface by communication system which uses the tree-phase motor power. This diagnostic information enables the implementation of predictive maintenance (condition monitoring) functions. For plant operators, this therefore makes it possible to detect faults in advance and implement measures to improve operational reliability and keep the downtimes of plants to a minimum. The prototype was designed to work in harsh conditions to reach a depth of 2000 m and temperatures up to 200 C. It used simulator software to define the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62-HP motor showed a good reliability and fast response of the prototype. © 2014 IEEE.

关键词： Contamination

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Algorithm for fast determination of LiFePO4 battery nominal current

Algorithm for fast determination of LiFePO4 battery nominal ...

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Proceedings of the International Convention MIPRO

作者： Igor Sirotić Viktor Šunde Željko Ban Faculty of Electrical Engineering and Computing Department of Electric Machines Drives and Automation Zagreb Croatia Faculty of Electrical Engineering and Computing Department of Control and Computing Engineering Zagreb Croatia

The development of production and increasing usage of light electric vehicles such as electric bicycles and electric scooters entails development of batteries, battery chargers and fast charging algorithms. Batteries with different nominal electrical characteristics and production technologies are currently in use. Among them, lithium-iron batteries are increasingly being used. The differences in basic characteristics of batteries and standardization issues require fast identification of various battery types and adapting of charging algorithms according to nominal current, voltage, capacity and state of charge. This paper describes a method for determining the nominal current for unknown LiFePO 4 battery connected to the stationary filling station for charging electric bicycles. A prerequisite for determination of the rated current is identification of current-voltage curve at the moment of connection and identification of the number of cells. The algorithm for determining these parameters is given in the first part of the paper. The second part deals with determination of the nominal current for LiFePO 4 battery based on current-voltage response to the selected battery charging algorithm.

关键词： Batteries System-on-chip Voltage measurement Temperature measurement Load modeling Current measurement Battery charge measurement

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A New Multi-Service Token Bucket-Shaping Scheme Based on 802.11e

A New Multi-Service Token Bucket-Shaping Scheme Based on 802...

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International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)

作者： Yunyi Zhang Shuru Liu Ran Zhang Wei Wei Houbing Song Wei Li Xiumei Fan College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China School of Computer Science and Engineering Xi'an University of technology State Key Laboratory for Strength and Vibration of Mechanical Structures of Xi’ an Jiaotong University Xi'an China Department of Electrical and Computer Engineering West Virginia University Institute of Technology West Virginia USA The Centre for Distributed and High Performance Computing School of Information Technologies The University of Sydney Sydney Australia School of Automation and Information Engineering Xi'an University of Technology Xi'an China

With the development of information technology, the demand for video transmission in wireless networks rapidly increases. The traditional traffic shaping algorithms cannot fully (or adequately) meet the demand for high-quality video transmission in wireless networks. Aiming to reduce this problem, this paper proposes a new multi-service flow, token bucket shaping scheme in an IEEE 802.11e environment. In view of the characteristics of video stream transmission in an IEEE 802.11e wireless network, this scheme adopts a multi-service token bucket technology on the basis of the traffic shaping scheme. After creating a simulation model in NS2, the simulation results show that the scheme can effectively improve the quality of service for video streaming in a wireless environment.

关键词： Streaming media IEEE 802.11e Standard Wireless networks Analytical models Data models Packet loss

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Hybrid Fuzzy and Robust Controller Applied to a DC-DC Boost Converter

Hybrid Fuzzy and Robust Controller Applied to a DC-DC Boost ...

引用

Annual Conference of the IEEE Industrial Electronics Society

作者： Joao T. de Carvalho Neto Andres O. Salazar Fabio M. U. de Araujo Anderson L. de O. Cavalcanti Department of Computing Engineering and Automation Federal University of Rio Grande do Norte

ISBN: (纸本)9781479940318

关键词： Hybrid Fuzzy Robust Control DC-DC converters Boost

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Graph cut and image segmentation using mean cut by means of an agglomerative algorithm

Graph cut and image segmentation using mean cut by means of ...

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9th International Conference on Computer Vision Theory and Applications, VISAPP 2014

作者： Chiba, Elaine Ayumi De Carvalho, Marco Antonio Garcia Da Costa, André Luis Computing Visual Lab. School of Technology - FT University of Campinas - UNICAMP Limeira - SP Brazil Department of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering - FEEC University of Campinas - UNICAMP Campinas-SP Brazil

ISBN: (纸本)9789897580031

Graph partitioning, or graph cut, has been studied by several authors as a tool for image segmentation. It refers to partitioning a graph into several subgraphs such that each of them represents a meaningful object of interest in the image. In this work we propose a hierarchical agglomerative clustering algorithm driven by the cut and mean cut criteria. Some preliminary experiments were performed using the benchmark of Berkeley BSDS500 with promising results. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

关键词： Image segmentation

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