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Chinese control and Decision Conference, CCDC

作者： Lihua Liu Xiukun Wei Tao Zhu Department of Computer Science and Automation Beijing Institute of Machinery Beijing China Delft Center of Systems and Control Delft University of Technnology Delft Netherlands

This paper addresses the issue on gain scheduled quasi linear parameter varying (LPV) control strategy for the air path system of diesel engines, which plays a critical role for the emission reduction of diesel engines. Due to the strong nonlinearities of the underlying system, traditional linear control algorithm can not achieve a satisfactory control performance. In this paper, the considered nonlinear plant is approximated as an Hammerstein quasi-LPV system in the first place. An advanced quasi-LPV gain scheduled control strategy is applied to the underlying system. The effectiveness of the new control algorithm is illustrated by the simulations.

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Fuzzy neural network approach for fault diagnosis of power plant thermal system under different operating points

Fuzzy neural network approach for fault diagnosis of power p...

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IEEE General Meeting Power& Energy Society

作者： Liangyu Ma Kwang Y. Lee Automation Department School of Control Science and Engineering North China Electric Power University Baoding Hebei China Department of Electrical and Computer Engineering Baylor University Waco TX USA

Developing a practical fault diagnosis system for a power plant thermal system is important in ensuring safe and reliable operation of the whole power generation unit. It is a difficult task due to the complex structure of the thermal system and the variable operating points of the system. Although artificial neural networks are very efficient in thermal system fault diagnosis, their applications for fault diagnosis usually consider only a single operating point (usually at the full rated load). Thus a fuzzy neural network approach for thermal system fault diagnosis under different operating points is investigated in this paper. An extended fuzzy fault symptom calculation method suitable for different load is discussed. The feedwater heater system of a 300 MW coal-fired power generation unit is taken as a fault diagnosis example. Several diagnosis tests for different faults under different operating points are carried out on a full-scope simulator of the power unit. The results under different operating points demonstrate the fault diagnosis ability of the fuzzy neural network method.

关键词： Fault diagnosis Water heating Artificial neural networks Optimization Load modeling Training Heat pumps

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Conflict resolution for collaborative design based on rough set theory

Conflict resolution for collaborative design based on rough ...

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International Conference on computer Supported Cooperative Work in Design

作者： Jun Ma Tian-Yuan Xiao Jian-Chao Zeng Ma Hao Department of Automation National CIMS Engineering Research Center Tsinghua University Beijing China School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan China North Automatic Control Technology Institute Taiyuan China

ISBN: (纸本)9781424416509

Due to the design knowledge discrepancy during collaborative design, conflicts can be revealed from the process of collaborative design decision. A critical element of collaborative design would be conflict resolution. The conflict resolution is correlative with both of the knowledge granulation and specific method provided. In this paper, granularity is used to describe rules acquainted based on the concept of rough degree. In this condition, A feasible distance formula between different rules is constructed according to the requirement of describing the distance between different rules and the definition of attribute significance in information system with rough theory, in which the operator of attribute importance is introduced, and then traditional conflict resolutions are analyzed. As a result, the concept of rule set evolution is put forward, and the instance is introduced to explain the efficiency of new method.

关键词： Collaboration Set theory Collaborative work Process design Design methodology Product design Phase detection Knowledge management Space technology Design automation

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New results on connecting the Lorenz and Chen Systems

New results on connecting the Lorenz and Chen Systems

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World Congress on Intelligent control and automation (WCICA)

作者： Dequan Li Lili Cui Zhixiang Yin Department of Mathematics and Physics Anhui University of Science and Technology Huainan China Laboratory of Complex Networks and Control Department of Automation Shanghai Jiaotong University Shanghai China School of Computer and Information Shanghai Second Polytechnic University Shanghai China

The Lu system is a newly coined chaotic system, which connects the Lorenz system and the Chen system and represents the transition from one to the other. In this letter, a simple nonlinear term is added to the Lu system, and its role as a joint function is revisited. With the gradual tuning the parameter of the nonlinear controller, the transition from the canonical Lorenz attractor to the Chen attractor through the Lu attractor is revived. The scheme herein goes beyond the traditional framework for studying the Lorenz-like systems, which can be very helpful in generating and analyzing of all similar and closely related chaotic systems.

关键词： Chaos Bifurcation Nonlinear dynamical systems control systems Chaotic communication Differential equations Numerical simulation

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Output feedback control of linear systems with input and output quantization

Output feedback control of linear systems with input and out...

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IEEE Conference on Decision and control

作者： Daniel Coutinho Minyue Fu Carlos E. de Souza Group of Automation and Control Systems Faculty of Engineering Pontifícia Universidade Católica do Rio Grande do Sul Porto Alegre Brazil School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW Australia Department of Systems and Control Laboratory Nacional de Computação Científica Petropolis Rio de Janeiro Brazil

ISBN: (纸本)9781424431236

A considerable amount of research has been done on the use of logarithmic quantizers for networked feedback control systems. However, most results are developed for the case of a single quantizer (either measurement or control signal quantization). In this paper, we investigate the case of simultaneous input and output quantization for SISO linear output feedback systems. Firstly, we show that the problem of quadratic stabilization via quantized feedback can be addressed with no conservativeness by means of the sector bound approach. Secondly, we provide a bound on the maximal admissible sector bound via a scaled H ¿ optimization problem.

关键词： Output feedback Linear feedback control systems control systems Linear systems Quantization Communication system control Feedback control Communication channels Digital control Bandwidth

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Research on rough set theory and applications in China

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Lecture Notes in computer science

作者： Wang, Guoyin Zhang, Qinghua Huang, Houkuan Ye, Dongyi Hu, Qinghua Hu, Xuegang Shi, Zhongzhi Li, Yongli Shang, Lin An, Liping Sai, Ying Chen, Shanben Liang, Jiye Qin, Keyun Zeng, Huanglin Xie, Keming Miao, Duoqian Min, Fan Wu, Zhaocong Wu, Weizhi Dai, Jianhua Institute of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China College of Math. and Computer Fuzhou University Fuzhou 350002 China Harbin Institute of Technology PO Box 458 Harbin 150006 China School of Computer and Information Hefei University of Technology Hefei 230009 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Lanzhou University No.222 Tianshui South Rd. Lanzhou 730000 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Management Science and Engineering Department Business School Nankai University Tianjin 300071 China Shandong University of Finance No.40 Shun-geng Road Jinan 250014 China Welding Engineering Institute Shanghai Jiaotong University Shanghai 200030 China School of Computer and Information Technology Shanxi University Taiyuan 030006 China Intelligent Control Development Center Southwest Jiaotong University Chengdu 610031 China Artificial Intelligence of Key Laboratory Sichuan University of Science and Engineering Zigong 643000 China Department of Automation College of Information Engineering Taiyuan University of Technology Taiyuan 030024 China 4800 CaoAn Highway Shanghai 201804 China School of Computer Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China School of Remote Sensing Information Engineering Wuhan University Wuhan 430079 China Institute for Information and System Sciences Faculty of Science Xi'an Jiaotong University Xi'an 710049 China Information College Zhejiang Ocean University Zhejiang 316004 China Institute of Artificial Intelligence Zhejiang University Hangzhou 310027 China

ISBN: (纸本)3540850635

This article gives a capsule view of research on rough set theory and applications ongoing at universities and laboratories in China. Included in this capsule view of rough set research is a brief description of the following things: Chinese research groups on rough set with their URLs for web pages, names of principal researchers (supervisors), numbers of graduate students, and topics being investigated. Statistical summaries showing the growth in the research on rough set theory and application in China are included. In addition, an introduction summarizing the research interests of Chinese researchers is included in this article. The contribution of this article is a complete overview of the principal research directions in rough set theory and its applications in China. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Neural networks for disturbance and friction compensation in hard disk drives

Neural networks for disturbance and friction compensation in...

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IEEE Conference on Decision and control

作者： Chow Yin Lai Frank L. Lewis V. Venkataramanan Xuemei Ren Shuzhi Sam Ge Thomas Liew Centre for Life Sciences (CeLS) Graduate School for Integrative Sciences and Engineering (NGS) National University of Singapore Singapore Automation and Robotics Research Institute University of Texas Arlington Fort Worth TX USA Data Storage Institute Engineering Agency for Science Technology and Research Singapore Department of Automatic Control Beijing Institute of Technology Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781424431236

In this paper, we show that the tracking performance of a hard disk drive actuator can be improved by using two adaptive neural networks, each of which is tailored for a specific task. The first neural network utilizes accelerometer signal to detect external vibrations, and compensates for its effect on hard disk drive position via feedforward action. In particular, no information on the plant, sensor and disturbance dynamics is needed in the design of this neural network disturbance compensator. The second neural network, designed to compensate for the pivot friction, uses a signum activation function to introduce nonlinearities inherent to pivot friction, thus reducing the neural network¿s burden of expectation. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the tracking performance of the hard disk drives can be improved significantly with the use of both neural networks compared to the case without compensation, or when only one of the networks is activated.

关键词： Neural networks Friction Hard disks Actuators Adaptive systems Feedforward neural networks Accelerometers Signal detection Stability analysis Stability criteria

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A design of 15 kW switched reluctance motor for electric vehicle applications

A design of 15 kW switched reluctance motor for electric veh...

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International Conference on Electrical Machines and Systems, ICEMS 2007

作者： Kachapornkul, S. Jitkreeyarn, P. Somsiri, P. Tungpimolrut, K. Akira, Chiba Tadashi, Fukao Industrial Control and Automation Laboratory Section National Electronics and Computer Technology Center Department of Electrical Engineering Faculty of Science and Technology Tokyo University of Science

In this paper, a design of the 3-phase, 6-stator-pole and 4-rotor-pole, 15 kW switched reluctance motor for the propulsion system of the electric vehicle is presented. Its performance such as the torque per volume and... 详细信息

ISBN: (纸本)8986510081

关键词： Electric vehicles

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An initial rotor position estimation method for switched reluctance motor without using machine parameter

An initial rotor position estimation method for switched rel...

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International Conference on Electrical Machines and Systems, ICEMS 2007

作者： Jitkreeyarn, P. Kachapornkul, S. Somsiri, P. Tungpimolrut, K. Akira, Chiba Tadashi, Fukao Industrial Control and Automation Laboratory Section National Electronics and Computer Technology Center Department of Electrical Engineering Faculty of Science and Technology Tokyo University of Science

ISBN: (纸本)8986510081

In this paper a method to estimate the initial rotor position of the switched reluctance motor (SRM) at the stand still condition is proposed. The proposed method can be implemented by the simple microcontroller based system, and it is not necessary to know the magnetization curves. The impulse gate drive signal is applied and the winding current is detected and its approximate value is used for calculating the rotor position. The compensation method to reduce the estimation error thorough one cycle is also mentioned. The proposed method is implemented with the 6-stator-pole and 4-rotor-pole, 1.5 kW 3-phase switched reluctance motor.

关键词： Error compensation

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