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检索条件"机构=School of Electrical and Computer Engineering Intelligent Systems and Control Laboratory"

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An Interval Type-II Robust Fuzzy Logic controller for a Static Compensator in a Multimachine Power System

An Interval Type-II Robust Fuzzy Logic Controller for a Stat...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： S. Mohagheghi G.K. Venayagamoorthy R.G. Harley Intelligent Power Infrastructure Consortium (IPIC) in the School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA University of KwaZulu-Natal South Africa

This paper presents a novel fuzzy logic based controller for a Static Compensator (STATCOM) connected to a power system. Type-II fuzzy systems are selected that enable the controller to deal with design uncertainties and the noise associated with the measurements in the power system. Interval type-II fuzzy is computationally more effective than the ordinary type-II fuzzy systems and is more suitable for the power network with fast changing dynamics. Using a proportional-integrator approach the proposed controller is capable of dealing with actual rather than deviation signals. The STATCOM is connected to a multimachine power system in order to provide extra voltage support and improve the system dynamic performance. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller during large scale faults as well as small disturbances. The type-II fuzzy membership functions provide a robust performance for the controller and eliminate the need for a model based adaptive control scheme.

关键词： Robust control Fuzzy logic control systems STATCOM Power systems Power system dynamics Power system measurements Fuzzy systems Automatic voltage control Power system simulation

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A fault-tolerant P-Q decoupled control scheme for static synchronous series compensator

A fault-tolerant P-Q decoupled control scheme for static syn...

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IEEE General Meeting Power& Energy Society

作者： Wei Qiao R.G. Harley G.K. Venayagamoorthy Intelligent Power Infrastructure Consortium (IPIC) in the School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA University of KwaZulu-Natal Durban South Africa Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

control of nonlinear devices in power systems relies on the availability and the quality of sensor measurements. Measurements can be corrupted or interrupted due to sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software (referred to as missing sensor measurements in this paper). This paper proposes a fault-tolerant control scheme (FTCS) for a static synchronous series compensator (SSSC). This FTCS consists of a sensor evaluation and (missing sensor) restoration scheme (SERS) cascaded with a P-Q decoupled control scheme (PQDC). It is able to provide effective control to the SSSC when single or multiple crucial sensor measurements are unavailable. Simulation studies are carried out to examine the validity of the proposed FTCS. During the simulations, single and multiple phase current sensors are assumed to be missing, respectively. Results show that the SERS restores the missing data correctly during steady and transient states, including small and large disturbances, and unbalanced three-phase operation. Thus, the FTCS continuously provides effective control to the SSSC with and without missing sensor measurements

关键词： Fault tolerance Communication system control Software measurement Nonlinear control systems control systems Power system faults Power system measurements Power system control Power systems Sensor systems

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Synchronous Reference Frame Based Active Filter Current Reference Generation Using Neural Networks

Synchronous Reference Frame Based Active Filter Current Refe...

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Annual Conference of Industrial Electronics Society

作者： Joy Mazumdar Ronald G Harley Ganesh K. Venayagamoorthy School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory University of Missouri Rolla Rolla MO USA

The increased use of nonlinear devices in industry has resulted in direct increase of harmonic distortion in the industrial power system in recent years. The significant harmonics are almost always 5th, 7th, 11th and the 13th with the 5th harmonic being the largest in most instances. Active filter systems have been proposed to mitigate harmonic currents of the industrial loads. The most important requirement for any active filter is the precise detection of the individual harmonic component's amplitude and phase. Fourier transform based techniques provide an excellent method for individual harmonic isolation, but it requires a minimum of two cycles of data for the analysis, does not perform well in the presence of subharmonics which are not integral multiples of the fundamental frequency and most importantly introduces phase shifts. To overcome these difficulties, this paper proposes a multilayer perceptron neural network trained with back-propagation training algorithm to identify the harmonic characteristics of the nonlinear load. The operation principle of the synchronous-reference-frame-based harmonic isolation is discussed. This proposed method is applied to a thyristor controlled DC drive to obtain the accurate amplitude and phase of the dominant harmonics. This technique can be integrated with any active filter control algorithm for reference generation

关键词： Active filters Synchronous generators Neural networks Power system harmonics Power harmonic filters Harmonic distortion Industrial power systems Phase detection Fourier transforms Data analysis

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Approximate Dynamic Programming Based on Expansive Projections

Approximate Dynamic Programming Based on Expansive Projectio...

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IEEE Conference on Decision and control

作者： Edilson F. Arruda Joao B. R. do Val Center For Systems and Control National Laboratory for Scientific Computing Petropolis Rio de Janeiro Brazil School of Electrical and Computer Engineering State University of Campinas Sao Paulo Brazil

ISBN: (纸本)1424401704;9781424401703

We present a general method to obtain convergent approximate value iteration algorithms with function approximation. The result is applicable to any arbitrary approximation architecture and generalizes existing results in the literature derived for particular approximation schemes. Additionally, we show how to obtain a convergent approximate mapping whose fixed point is the projection in the approximation space of a fixed point of the exact dynamic programming mapping with regards to a suitable subset norm. This result relies on evaluating the difference between successive iterates in the selected subset norm, which provides convergent procedures for any arbitrary approximation architecture

关键词： Dynamic programming Function approximation Convergence Approximation algorithms Monitoring computer architecture State-space methods USA Councils Large-scale systems Heuristic algorithms

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Significance of Pacemaker vs. Non-Pacemaker Neurons in an Excitatory Rhythmic Network

Significance of Pacemaker vs. Non-Pacemaker Neurons in an Ex...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Liston K. Purvis Terrence M. Wright Jeffrey C. Smith Robert J. Butera Laboratory for Neuroengineering Georgia Institute of Technology Atlanta GA USA Department of Biology Emory University Atlanta GA USA Cellular and Systems Neurobiology Section Laboratory of Neural Control NINDS-National Institutes of Health Bethesda MD USA Laboratory for Neuroengineering and School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

This modeling study investigates the functional role of pacemaker neurons in generating stable rhythms in the pre-Botzinger complex, a subcircuit of the respiratory pattern-generating circuitry in mammals. While the presence of pacemakers within the network is without doubt, the percentage and significance of such pacemakers is still unresolved. Here we revisited earlier network simulations by varying the fraction of pacemaker and non-pacemaker neurons within the network, and quantifying the robustness of the input parameter space and range of frequencies output by the network. Stable network rhythms were possible even with no pacemakers. However, we found that a network of at least 50% pacemakers produced the greatest range of output frequencies and had the more robust input space

关键词： Pacemakers Neurons Frequency Rhythm Robustness Circuits Laboratories Neural engineering Cities and towns USA Councils

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Asynchronous event-based communication across Service Brokers

Asynchronous event-based communication across Service Broker...

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12th European Wireless Conference 2006 - Enabling Technologies for Wireless Multimedia Communications

作者： E. Koutsoloukas S. Kapellaki G. N. Prezerakos N. Tselikas I. S. Venieris D. I. Kaklamani Intelligent Communications and Broadband Networks Laboratory School of Electrical and Computer Engineering National Technical University of Athens 9 Heroon Polytechneioy str Zografou Greece Technological Education Institute of Piraeus Faculty of Technology Dpt. of Electronic Computing Systems Petrou Ralli & Thivon 250 122 44 Athens Greece

Modern communication environments tend to be complex, dynamic and highly distributed. For the provision of messaging in such environments multiple entities, providing different functionalities and located remotely from each other, must cooperate in order to perform different tasks and provide different kind of information for the completion of the service provision lifecycle. Within this paper we present an implementation analysis of the communication mechanism which was employed in a distributed brokerage framework for the provision of context aware personalized services. The paper focuses on the inter-broker communication mechanism which enables the transparent interaction between components located in different brokers. The mechanism was designed and implemented having in mind relevant requirements such as transparency, modularity and high availability. The design and implementation was based on web service practices and the SOAP protocol.

关键词： Laboratories

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

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Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Ranked centroid projection: A data visualization approach for self-organizing maps

Ranked centroid projection: A data visualization approach fo...

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International Joint Conference on Neural Networks, IJCNN 2005

作者： Yen, Gary G. Wu, Zheng Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 United States

The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data as it performs a topology-preserving projection of the input space on a low-dimensional grid. To utilize the information provided by the SOM and obtain an approximation of the data structure, a separate data projection method is usually needed. However, most of the SOM projection methods are computationally expensive when the size of the data set becomes large. In this paper we present an intuitive and effective SOM projection method with comparatively low computational complexity for the purpose of cluster visualization. This method maps data vectors on the output space based on their responses to different prototype vectors. High-resolution maps can be obtained with a relatively small network size. The proposed method is demonstrated using both an artificial and a real world data set. © 2005 IEEE.

关键词： Self organizing maps

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Fault classification on vibration data with wavelet based feature selection scheme

Fault classification on vibration data with wavelet based fe...

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IECON 2005: 31st Annual Conference of IEEE Industrial Electronics Society

作者： Yen, Gary G. Leong, Wen Fung Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 United States

ISBN: (纸本)0780392523

Fault classification based upon vibration data is an essential building block of a sophisticated conditional based monitoring (CBM) system. Multiple sensor channels are called for to assure the redundancy and to achieve the desired reliability and accuracy. The shortcoming of using multiple sensor input channels is the need to deal with high dimensional features set, a computational expensive task in classification. It is vital to reduce the feature dimension via an effective feature extraction and feature selection scheme. A simple wavelet based feature selection scheme is proposed. This scheme overcomes the disadvantages faced by existing feature selection methods, by producing a general feature set, reducing the dimensionality of features and requiring no prior information of the problem domain. The proposed feature selection scheme is based on the strategy of "divide and conquer" that significantly reduce the computation time without compromising the classification performance. The simulation results show the proposed feature selection scheme provides at least 65% reduction of the total number of features without compromising the classification performance. © 2005 IEEE.

关键词： Wavelet transforms

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Iterative MOESP type algorithm for discrete time variant system identification

Iterative MOESP type algorithm for discrete time variant sys...

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20th IEEE International Symposium on intelligent control, ISIC '05 and the13th Mediterranean Conference on control and Automation, MED '05

作者： Tamariz, Annabell D. R. Bottura, Celso P. Barreto, Gilmar Nucleus of Research and Development in Computer Science University Cndido Mendes UCAM-Campos Rio de Janeiro Brazil Control and Intelligent Systems Laboratory School of Electrical and Computer Engineering State University of Campinas So Paulo Brazil

ISBN: (纸本)0780389360

With the main objective to develop an iterative state-space identification algorithm for linear multivariable discrete time-variant systems, in this study we propose and implement a computational procedure we call MOESP_VAR that is based in subspace methods of the type "Multivariable Output-Error State sPace" (MOESP). In addition the algorithm is tested with criterion and experimentation that we also propose. ©2005 IEEE.

关键词： Discrete time control systems

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