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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Michel Hell Pyramo Costa Fernando Gomide Department of Computer Engineering and Automation (DCA) Faculty of Electrical and Computer Engineering (FEEC) State University of Campinas Sao Paulo Brazil Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Belo Horizonte Minas Gerais Brazil

In this paper we introduce a new approach to train neurofuzzy networks using the participatory learning concept. The participatory learning paradigm tends to emulate the human learning mechanism where an acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The performance of the proposed learning scheme is illustrated by an example involving a nonlinear system modeling problem: the thermal modeling of power transformers. Comparisons with other methods reported in the literature and between two dual network structures are also included. The experimental results show the effectiveness of participatory learning in neurofuzzy networks training.

关键词： Power system modeling Fuzzy systems Power transformers Training data Humans Nonlinear systems Neural networks Fuzzy sets Power engineering computing Power engineering and energy

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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 2007(ICEMS2007)(第十届国际电机与系统会议)

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

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： Switched reluctance motor initial rotor position estimation

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NEURAL-ADAPTIVE CONTROL BASED ON ADALINE NEURONS WITH APPLICATION TO A POWER SYSTEM

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IFAC Proceedings Volumes 2007年第18期40卷 457-464页

作者： Ioan Filip Octavian Prostean Florin Dragan Cristian Vasar Department of Control System Engineering “Politehnica” University from Timisoara Faculty of Automation and Computer Science 300223 Timisoara Romania Phone: (+40) 0256-403238 E-Mail: ioan.filip@aut.upt.ro

A neural-adaptive control solution is exposed in this paper. The control strategy is based on the linear adaptive neuron, which is called ADALINE. Unlike other neural control solutions, based on perceptrons neurons characterized by a long time learning process and a difficult on-line tuning of weights, this approach uses a fast algorithm, which adapts on-line the neuron's weights. Therefore the non-linear character of control law is induced by the permanent changes of neuron weights, which are variable parameters of controller. A set of study cases is done, with application to the excitation control of a synchronous generator.

关键词： adaptive control neural networks ADALINE modelling simulation synchronous generator

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SHORT TERM ELECTRIC LOAD FORECAST WITH ARTIFICIAL NEURAL NETWORKS

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IFAC Proceedings Volumes 2007年第18期40卷 443-449页

作者： Vasar Cristian Szeidert Iosif Filip Ioan Prostean Gabriela Department of Control System Engineering “Politehnica” University from Timisoara Faculty of Automation and Computer Science 300223 Timisoara Romania Phone: (+40) 256-403237 E-Mail: cristian.vasar@aut.upt.ro

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment.

关键词： neural networks prediction problems load forecasting feedforward networks simulation

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Federated filtering for fault tolerant estimation and sensor redundancy management in coupled dynamics distributed systems

Federated filtering for fault tolerant estimation and sensor...

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Mediterranean Conference on Control and automation (MED)

作者： A. Edelmayer M. Miranda Faculty of Engineering Department of Chemical Engineering Laboratory of Unit Operations University de Los Andes Merida Venezuela Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary

This paper discusses the application of the idea of federated filtering to the estimation of intrinsically nonlinear distributed systems by examining its impacts on filtering performance by using the Extended Kalman Filter (EKF) as state estimator. Specifically, the performance of the traditional centralized solution is compared with the filtering structure obtained using the federating idea, and their conceptions, and their ability to balance between fault tolerance and estimation accuracy is examined. Our research demonstrates how successfully the EKF for solving nonlinear estimation problems in federated structures can be used, noting that the idea of federation have only been demonstrated for linear problems previously. In addressing the demands of both fault tolerance and estimation accuracy, it is shown that increased filtering accuracy is relied on the proper choice of sharing of the error covariance information between local filters, while sensor fault tolerance is provided by the utilization of an appropriate resetting policy of the filter.

关键词： Fault tolerant systems Sensor systems Redundancy Nonlinear filters Fault tolerance Control systems Information filtering Information filters computer architecture Sensor arrays

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Decentralized Synchronization of an Uncertain Complex Dynamical Network

Decentralized Synchronization of an Uncertain Complex Dynami...

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American Control Conference (ACC)

作者： Wei-Song Zhong Georgi M. Dimirovski Jun Zhao Key Laboratory Integrated Automation of Process Industry-Ministry of Education and School of Information Science Engineering Respectively Northeastern University Shenyang Liaoning China SS Cyril and Methodius Faculty of Electrical Engineering Information Technologies Skopje Macedonia Department of Computer Engineering Dogus University Kadikoy Turkey

A class of uncertain time-varying complex dynamical networks is studied in this paper and a model introduced. On the grounds of that model then the locally and globally decentralized synchronization of these networks are thoroughly investigated. Several network synchronization criteria are deduced. Especially, the assumptions adopted and decentralized control laws designed are considerably simple. An illustrative example along with the respective numerical and computer simulation results is also given to demonstrate the effectiveness of the proposed synchronization control synthesis.

关键词： Complex networks Network synthesis Large-scale systems Robust control Distributed control Control systems Network topology Robustness Chaos Robust stability

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Weighted Centroid Localization in Zigbee-based Sensor Networks

Weighted Centroid Localization in Zigbee-based Sensor Networ...

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IEEE International Symposium on Intelligent Signal Processing

作者： Jan Blumenthal Ralf Grossmann Frank Golatowski Dirk Timmermann Faculty of Computer Science and Electrical Engineering Institute of Applied Microelectronics and CE Warnemunde Germany Inst. of Appl. Microelectron. & CE Rostock CELISCA Center for Life Science Automation University of Rostock Germany

ISBN: (纸本)9781424408290;1424408296

Localization in wireless sensor networks gets more and more important, because many applications need to locate the source of incoming measurements as precise as possible. Weighted centroid localization (WCL) provides a fast and easy algorithm to locate devices in wireless sensor networks. The algorithm is derived from a centroid determination which calculates the position of devices by averaging the coordinates of known reference points. To improve the calculated position in real implementations, WCL uses weights to attract the estimated position to close reference points provided that coarse distances are available. Due to the fact that Zigbee provides the link quality indication (LQI) as a quality indicator of a received packet, it can also be used to estimate a distance from a node to reference points.

关键词： Wireless sensor networks ZigBee Time measurement Intelligent sensors Signal processing automation computer science Microelectronics Application software Electric variables measurement

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A Simplified Variable Speed Switched Reluctance Motor Drive without Using Encoder

A Simplified Variable Speed Switched Reluctance Motor Drive ...

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International Conference on Electrical Machines and Systems 2007(ICEMS2007)(第十届国际电机与系统会议)

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

The switched reluctance motor (SRM) and drive system is a candidate in various applications including the home appliance. The simple and low cost system with an adequate performance is also one topic to be developed. A speed sensor directly increases the cost and it directly influences the reliability of the system. This paper proposes a simplified variable speed control system for the SRM without using an encoder. The method is not based on the exact rotor position estimation, only the turn off angle is determined from the simple relation between measured terminal voltage and current. The effectiveness of the proposed method is verified by the experimental result on the 3 kW 3-phase 6-stator-pole and 4-rotor-pole SRM.

关键词： Switched reluctance motor variable speed drive system turn off angle rotor position estimation

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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 2007(ICEMS2007)(第十届国际电机与系统会议)

作者： P. Jitkreeyarn K. Tungpimolrut S. Kachapornkul P. Somsiri Tadashi Fukao Akira Chiba Industrial Control and Automation Laboratory Section National Electronics and Computer Technology C 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

关键词： Switched reluctance motor motor design electric vehicle

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MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN CONTROL

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Asian Journal of Control 2008年第2期6卷

作者： Suresh Kalyanasundaram Edwin K. P. Chong Ness B. Shroff Motorola India Electronics Limited No. 66/1 Plot 5 Bagmane Techpark C. V. Raman Nagar Post Bangalore 560 093 India. Department of Electrical and Computer Engineering Colorado State University Fort Collins CO 80523-1373 USA. Professor Edwin K. P. Chong received the B.E.(Hons.) degree with First Class Honors from the University of Adelaide South Australia in 1987 graduating top of his class and the M.A. and Ph.D. degrees in 1989 and 1991 respectively both from Princeton University where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991 where he was named a University Faculty Scholar in 1999 and promoted to Full Professor in 2001. Since August 2001 he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University. His current interests are in communication networks and optimization methods. He coauthored the best-selling book An Introduction to Optimization 2nd Edition Wiley-Interscience 2001. He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He coauthored a paper that was awarded Best Paper in the journal Computer Networks 2003. Professor Chong is a Fellow of the IEEE. He was founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems and until recently served as an IEEE Control Systems Society Distinguished Lecturer. He has been on the editorial board of the IEEE Transactions on Automatic Control. He is currently on the editorial board of the journal Computer Networks. He has also served on the organizing committees of several international conferences. He has been on the program committees for the IEEE Conference on Decision and Control the American Control Conference the IEEE International Symposium on Intelligent Control IEEE Symposium on Computers and Communications and the IEEE Global Telecommunications Conference. He has also served in the executive committees for the IEEE Co

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per-unit-time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max-min optimal policy, which maximizes the worst-case average per-unit-time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time-varying transition rates.

关键词： Markov decision processes sensitivity max-min control call admission control policy iteration

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