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Distributed, master-less control of modular DC-DC converters

Distributed, master-less control of modular DC-DC converters

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Collection of Technical Papers - 2nd International Energy Conversion engineering Conference

作者： Gray, Michael S. Gao, Zhiqiang Button, Robert M. Cleveland State University Cleveland OH 44115 United States NASA Glenn Research Center Cleveland OH United States Department of Electrical and Computer Engineering United States Center for Advanced Control Technologies United States Electrical Systems Research Branch M.S 333-2 21000 Brookpark Rd. United States

ISBN: (纸本)1563477157

A distributed control system (DCS) is developed and hardware verified for a class of digitally controlled modular DC-DC converters. The converters are each independently controlled by its own FPGA-based digital controller. A control Area Network (CAN) is first set up for the converters to communicate in a master-less peer-to-peer manner. An algorithm is developed to make the converters share the load (current) dynamically in a predetermined manner. More importantly, it makes it possible to for all converters to automatically time-shift their PWM gating signals to minimize the current ripple, which is known as interleaving. An algorithm is developed for this distributed master-less control of power converter system so that the load sharing and interleaving are adjusted autonomously, in real time, as the number of converters changes without prior knowledge. Copyright © 2004 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： DC motors

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Speed control of an interior permanent magnet synchronous motor using belbic (brain emotional learning based intelligent controller)

Speed control of an interior permanent magnet synchronous mo...

引用

Proceedings of the Biannual World Automation Congress

作者： R. Mohammdi-Milasi C. Lucas B. Nadjar-Arrabi Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran Tehran Iran Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran and School of Cognitive Sciences (SCS) Tehran Iran Center of Excellence for Control and Intelligent Processing Department of Electrical and Coinputer Enginecring University of Tehran and School of Cognitive Scienccs (SCS) Tehran Iran

Among ac drives, the permanent magnet synchronous motor has been gaining popularity owing to its high torque to current ratio, large power to weight ratio, high efficiency, high power factor and robustness. Because of its technical and economic advantages, Permanent Magnet Synchronous Motor drive technology is a serious contender for replacing the existing technologies. In this paper we report the utilization of a novel controller (BELBlC) based on emotion processing mechanism in brain. Our results show superior control characteristics especially very fast response, simple implementation and robustness with respect to disturbances and manufacturing imperfections. Our proposed method enables the designer to shape the response in accordance with the multiple objectives of his/her choice.

关键词： Velocity control Permanent magnet motors Torque control Rotors AC motors Machine vector control Synchronous motors Process control Magnetic materials control theory

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Diversity control approach to ant colony optimization for unit commitment problem

Diversity control approach to ant colony optimization for un...

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IEEE Region 10 International Conference TENCON

作者： D. Nualhong S. Chusanapiputt S. Phomvuttisarn T. Saengsuwan S. Jantarang Electrical Engineering Department Electrical and Control System Engineering Division Electricity Generating Authority of Thailand Bangkok Thailand Department of Electrical Power Engineering Faculty of Engineering Mahanakorn University Bangkok Thailand Center of Excellence in Electrical Power Technology Faculty of Engineering Chulalongkom University Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Kasetsart University Bangkok Thailand Department of Computer Engineering and Satellite Research Center Faculty of Engineering Mahanakom University of Technology Bangkok Thailand

This paper presents a new method to solve the constrained unit commitment problem by applying ant colony optimization (ACO) based on the diversity control approach. The pheromone updating rule is modified to control the diversification by adopting a simple mechanism for random selection in ACO. The proposed method is tested on the 10-unit test system with a scheduling time horizon of 24 hours. The numerical results show an economical saving in the total operating cost when compared to the previous literature results. Moreover, two types of the proposed diversity control technique have the features of easy implementation and a better convergence rate superior to a standard ACO.

关键词： Ant colony optimization

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Reactive tabu search for optimal power flow under constrained emission dispatch

Reactive tabu search for optimal power flow under constraine...

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IEEE Region 10 International Conference TENCON

作者： D. Nualhong S. Chusanapiputt S. Phomvuttisarn S. Jantarang Electrical Engineering Department Electrical and Control System Engineering Division Electricity Generating Authority of Thailand Bangkok Thailand Department of Electrical Power Engineering Faculty of Engineering Mahanakom University of Technology Bangkok Thailand Center of Excellence in Electrical Power Technology Faculty of Engineering Chulalongkom University Bangkok Thailand Department of Computer Engineering and Satellite Research Center Faculty of Engineering Mahanakom University of Technology Bangkok Thailand

This paper presents an efficient method to obtain the optimal power flow (OPF) problem under constrained emission dispatch by applying reactive tabu search (RTS) algorithm. The RTS is developed as a derivative-free optimization technique in solving constrained emission OPF problem significantly reduces the computational burden with the strategies that make the search process robust and fast. The effectiveness of the proposed approach has been demonstrated through the IEEE 30-bus, 6-generator, test system. The simulation results reveal that the proposed RTS can yield highly optimal solution and tan reduce computational execution time superior to a standard tabu search. Moreover, the proposed method provides better solution than previous literatures with promising results.

关键词： Load flow

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Abnormality detection of a continuous pan in a sugar mill

Abnormality detection of a continuous pan in a sugar mill

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Liuping Wang A. Giles R. Peirce School of Electrical and Computer Engineering Royal Melbourne Institute of Technology Melbourne Australia Center for Integrated Dynamics and Control Department of Electrical and Computer Engineering University of Newcastle Australia CSR Victoria Mill QLD Australia

This paper reports an industrial application of principle component analysis to process abnormality detection in a sugar mill. The process under investigation is a continuous pan which is one of the most crucial processes in sugar production. Two sets of experimental results are obtained in this work: one is related to an artificially induced fault by a stuck valve; the other captures a naturally occurred fault due to equipment failure. The principle component analysis algorithm successfully detects both faults. Only the latter case is reported in this paper.

关键词： Milling machines Sugar industry Monitoring control charts Modems Principal component analysis Predictive models computer industry electrical products industry Industrial control

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A novel controller for a power system based belbic (brain emotional learning based intelligent controller)

A novel controller for a power system based belbic (brain em...

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Proceedings of the Biannual World Automation Congress

作者： R. Mohammdi-Milasi C. Lucas B. Najar-Arrabi Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran Tehran Iran Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Engineering School of Intelligent Systems (SIS) Institute for Studies in Theoretical Physics and Mathematics (IPM) University of Tehran Tehran Iran

In this paper we report the utilization of a novel controller (BELBIC) based un emotion processing mechanism in brain for power system. Using the BELBIC controller, both transient stability and voltage regulation of power systems are achieved. The special characteristic of this controller that makes it effective is its flexibility its five gain parameters that give good freedom for choosing favorite response. With this degree of freedom choosing of these parameters involves trade-off between overshoot and speed of response. The effectiveness of the proposed BELBIC controller is shown through some computer simulations on a (SMIB) power system.

关键词： control systems Power system control Power systems Power system stability Power system modeling Power system transients Power system faults Power system dynamics Voltage control Process control

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Digital PI fuzzy control strategies applied to an electric microgenerator system

Digital PI fuzzy control strategies applied to an electric m...

引用

IEEE/PES Transmission and Distribution Conference and Exposition: Latin America

作者： B.M. Campos C.T. da Costa W. Barra K.C.F. da Silva J.A.L. Barreiros Laboratory of Control and Systems (LACOS) Technological Center Electrical and Computer Engineering Department Federal University of Para Belem Para Brazil

This paper investigates digital modeling and control strategies applied to the voltage regulation of a microgenerator system, placed in the Electric Energy Generation Laboratory of Federal University of Para. Identification parametric techniques are used in order to obtain a representative model for the controller design. With a suitable model, controllers of proportional integral type are designed, based on the root locus and fuzzy systems strategies, in order to improve the voltage regulation of the microgenerator system.

关键词： Fuzzy control Voltage control Digital control Proportional control Fuzzy logic Regulators control systems DC motors Velocity control Laboratories

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EEG-based fuzzy neural network estimator for driving performance

EEG-based fuzzy neural network estimator for driving perform...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ruei-Cheng Wu Chin-Teng Lin Sheng-Fu Liang Teng-Yi Huang Tzyy-Ping Jung Brain Research Center Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan Institute for Neural Computation University of California San Diego CA USA

ISBN: (纸本)0780385675

Accidents caused by drivers' drowsiness have a high fatality rate because of the marked decline in the drivers' vehicle control abilities. Preventing accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers. This paper proposes a brain-machine interface that combines electroencephalographic power spectrum estimation, principal component analysis, and fuzzy neural networks to estimate/predict drivers' drowsiness level in a virtual-reality-based driving simulator. The driving performance is defined as deviation between the center of the vehicle and the center of the cruising lane. Our results demonstrated that the proposed method is feasible to accurately estimate quantitatively driving performance in a realistic driving simulator.

关键词： Fuzzy neural networks Vehicle driving Electroencephalography Accidents Safety Fatigue Vehicle detection Brain modeling computational modeling Traffic control

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Induction machine broken bar detection using neural networks based classification

Induction machine broken bar detection using neural networks...

引用

IEEE Conference on Cybernetics and Intelligent Systems

作者： M.R. Rafimanzelat B.N. Araabi E. Khosroshahli Niroo Research Institute Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Iran

This paper addresses the developing of a fault diagnosis system for detection of broken rotor bars, a common mechanical fault in cage induction machines, using efficient feature extraction techniques and a neural network classifier. The proposed algorithm uses the stator current and motor speed as inputs. Fast Fourier Transform is utilized to obtain the frequency spectrum of the current signal. An efficient algorithm is then used to extract suitable features out of the frequency spectrum of the signal. The relevance of the features for the purpose of fauIt detection is investigated and verified. A neural network classifier is then developed and applied to distinguish different motor conditions. A series of data collected from experiments on a three phase 3 hp cage induction machine performed in different load and fauIt conditions are used to provide data for training and then testing the classifier. Experimental results confirm the etkiency of the proposed algorithm for detection of broken bar faults.

关键词： Induction machines Neural networks Rotors Feature extraction Induction motors Thermal stresses Frequency Fault diagnosis Bars Fault detection

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Estimating driving performance based on EEG spectrum and fuzzy neural network

Estimating driving performance based on EEG spectrum and fuz...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ruei-Cheng Wu Chin-Teng Lin Sheng-Fu Liang Te-Yi Huang Yu-Chieh Chen Tzyy-Ping Jung Brain Research Center Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan Institute for Neural Computation University of California San Diego CA USA

ISBN: (纸本)0780383591

The growing number of traffic fatalities in recent years has become a serious concern to society. Accidents caused by drivers' drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the drivers' abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing accidents caused by drowsiness requires a technique for detecting, estimating, and predicting the level of alertness of a driver and a mechanism for maintaining his/her maximum performance. This work describes a system that combines electroencephalographic (EEG) power spectrum estimation, principal component analysis, and fuzzy neural network model to estimate/predict drivers' drowsiness level in a driving simulator. Our results demonstrated that, for the first time, it is feasible to accurately estimate task performance, accurately estimate quantitatively measured driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulation.

关键词： Electroencephalography Fuzzy neural networks Brain modeling Fuzzy control Accidents Vehicle driving Predictive models Communication system traffic control Wheels Spectral analysis

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