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Dynamic modeling of wind farms with fixed-speed wind turbine generators

Dynamic modeling of wind farms with fixed-speed wind turbine...

引用

2007 IEEE Power engineering Society General Meeting, PES

作者： Wei, Qiao Harley, Ronald G. Venayagamoorthy, Ganesh K. IEEE School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States University of KwaZulu-Natal Durban South Africa Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri-Rolla Rolla MO 65409-0249 United States

ISBN: (纸本)1424412986

A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. Concluding remarks are provided on how to choose an appropriate wind farm model for power system dynamic and transient studies. © 2007 IEEE.

关键词： Power plants

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Recent advances in networked control systems

Recent advances in networked control systems

引用

International Conference on Control, Automation and systems, ICCAS 2007

作者： Sun, Zengqi Li, Hongbo Wang, Yan Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 China

ISBN: (纸本)8995003871

This paper presents a comprehensive overview of the current state of research in the area of Networked control systems (NCSs) first. Then two modeling and control methods are introduced for NCSs in details. The first one is a stochastic control method, which investigates the H∞ control problem for NCSs with random network-induced delay. The second one is a switch control method, which focuses on solving the stabilization problem for NCSs in discrete-time domain, where both network-induced delay and packet dropout are taken into account. Illustrative examples are given to demonstrate the effectiveness of the proposed approaches. Finally, this paper concludes with the discussion of possible future development of NCSs from a control perspective.

关键词： Networked control systems

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Quantum robots for teenagers

Quantum robots for teenagers

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37th International Symposium on Multiple-Valued Logic, ISMVL 2007

作者： Raghuvanshi, Arushi Fan, Yale Woyke, Michal Perkowski, Marek Intelligent Robotics Laboratory Department of Electrical and Computer Engineering Portland State University Portland OR Valley Catholic Middle School Beaverton OR United States Catlin Gabel School Portland OR 97225-6599 United States Gymnasium Number 20 Raszyńska 22 Warsaw Poland

ISBN: (纸本)0769528317

Extending the ideas of Quantum Braitenberg Vehicles from [14], we present here a family of Lego robots controlled by multiple-valued quantum circuits. The robots have at most 6 degrees of freedom (motors) and 6 sensors. Their basic architecture is a generalization of robots from [16] to more versatile multiple-valued quantum automata (simulated in software). We believe that building robots with "quantum brains" is an excellent future application of quantum computing and now it helps students to learn principles of quantum circuits. We present a one-year project in "quantum robotics for teenagers". Our project brings research and educational perspectives, which are both presented in this paper. © 2007 IEEE.

关键词： intelligent robots

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A geometric optimization approach to detecting and intercepting dynamic targets

A geometric optimization approach to detecting and intercept...

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2007 American Control Conference, ACC

作者： Ferrari, Silvia Cai, Chenghui Fierro, Rafael Perteet, Brent Laboratory for Intelligent Systems and Controls Department of Mechanical Engineering and Materials Science Duke University Durham NC 27708-0300 United States MARHES Lab. School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078-5032 United States

ISBN: (纸本)1424409888

A methodology is developed to deploy a mobile sensor network for the purpose of detecting and capturing mobile targets in the plane. The sensing-pursuit problem considered in this paper is analogous to the Marco Polo game, in which the pursuer must capture multiple mobile targets that are sensed intermittently, and with very limited information. In this paper, the mobile sensor network consists of a set of robotic sensors that must track and capture mobile targets based on the information obtained through cooperative detections. Since the sensors are installed on robotic platforms and have limited rangce, the geometry of the platforms and of the sensors field-of-view play a key role in obstacle avoidance and target detection. Thus, a new cell decomposition approach is presented to formulate the probability of detection and the cost of operating the robots based on the geometric properties of the network. Numerical simulations verify the validity and flexibility of our methodology. ©2007 IEEE.

关键词： Sensor networks

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Collaborative Routing Algorithm for Wireless Sensor Network Longevity

Collaborative Routing Algorithm for Wireless Sensor Network ...

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intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： Shishir Bashyal Ganesh Kumar Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

This study proposes a new parameter for evaluating longevity of wireless sensor networks after showing that the existing parameters do not properly evaluate the performance of algorithms in increasing longevity. This study also proposes an ant inspired Collaborative Routing Algorithm for Wireless Sensor Network Longevity (CRAWL) that has scalability and adaptability features required in most wireless sensor networks. Using the proposed longevity metrics and implementing the algorithm in simulations, it is shown that CRAWL is much more adaptive to non-uniform distribution of available energy in sensor networks. The performance of CRAWL is compared to that of a non-collaborative algorithm. Both algorithms perform equally well when the available energy distribution is uniform but when the distribution is non-uniform, CRAWL is found to have 20.2% longer network life. CRAWL performance degraded by just 10.1% when the available energy was unevenly distributed in the sensor network proving the algorithms adaptability.

关键词： Collaboration Routing Wireless sensor networks Scalability Energy resources Protocols Sensor phenomena and characterization Monitoring intelligent sensors Energy consumption

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Blind Deconvolution De-noising for Helicopter Vibration Data

Blind Deconvolution De-noising for Helicopter Vibration Data

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American Control Conference (ACC)

作者： Bin Zhang Taimoor Khawaja Romano Patrick George Vachtsevanos Intelligent Control Systems Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Critical aircraft assets are required to be available when needed, while exhibiting attributes of reliability, robustness and high confidence under a variety of flight regimes, and maintained on the basis of their current condition rather than on the basis of scheduled maintenance practices. New and innovative technologies must be developed and implemented to address these concerns. Condition based maintenance (CBM) requires that the health of critical components/systems be monitored and diagnostics/prognostic strategies be developed to detect and identify incipient failures and predict the failing component's remaining useful life (RUL). Typically, vibration and other key indicators on-board on aircraft are severely corrupted by noise thus curtailing our ability to accurately diagnose and predict failures. This paper introduces a novel blind deconvolution de-noising scheme that employs vibration model in the frequency domain and attempts to arrive at the true vibration signal through an iterative optimization process. Performance indexes are defined and data from a helicopter are used to demonstrate the effectiveness of the proposed scheme.

关键词： Deconvolution Noise reduction Helicopters Maintenance Aircraft Robustness Condition monitoring Frequency domain analysis Signal processing Performance analysis

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An Estimation of Distribution Improved Particle Swarm Optimization Algorithm

An Estimation of Distribution Improved Particle Swarm Optimi...

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intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： R. V. Kulkarni G. K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to optimization problems in areas including sensor networks.

关键词： Particle swarm optimization Ant colony optimization Electronic design automation and methodology Probability distribution Benchmark testing Optimization methods Equations Genetic mutations Space exploration Real time systems

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Self-healing control with multifunctional gate drive circuits for power converters

Self-healing control with multifunctional gate drive circuit...

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2007 IEEE Industry Applications Conference 42nd Annual Meeting, IAS

作者： Peng, Xiao Venayagamoorthy, Ganesh K. Corzine, Keith A. Woodley, Robert Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri-Rolla United States 21st Century Systems Inc. 199 E 4th St. Ft. Leonard Wood MO United States

ISBN: (纸本)1424403642

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its prefault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults. © 2007 IEEE.

关键词： Power converters

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Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework

Novel Architecture for supporting medical decision making of...

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

作者： Elpiniki Papageorgiou Chrysostomos Stylios Peter Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Greece Intelligent Computing Laboratory Department of Informatics and Telecommunications Technology TEI Epirus Greece

Medical problems involve different types of variables and data, which have to be processed, analyzed and synthesized in order to reach a decision and/or conclude to a diagnosis. Usually, information and data set are both symbolic and numeric but most of the well-known data analysis methods deal with only one kind of data. Even when fuzzy approaches are considered, which are not depended on the scales of variables, usually only numeric data is considered. The medical decision support methods usually are accessed in only one type of available data. Thus, sophisticated methods have been proposed such as integrated hybrid learning approaches to process symbolic and numeric data for the decision support tasks. Fuzzy cognitive maps (FCM) is an efficient modelling method, which is based on human knowledge and experience and it can handle with uncertainty and it is constructed by extracted knowledge in the form of fuzzy rules. The FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This rule base could be derived by a number of machine learning and knowledge extraction methods. Here it is introduced a hybrid attempt to handle situations with different types of available medical and /or clinical data and with difficulty to handle them for decision support tasks using soft computing techniques.

关键词： Decision making Fuzzy cognitive maps Medical diagnostic imaging Data mining Decision support systems Learning systems Computational intelligence computer networks Diseases Spatial databases

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Identification of Induction Machines Stator Currents with Generalized Neurons

Identification of Induction Machines Stator Currents with Ge...

引用

2007 IEEE Power engineering Society Conference and Exposition in Africa (IEEE PES PowerAfrica 2007), part 2

作者： Jing Huang Ganesh K. Venayagamoorthy Keith Corzine Real-Time Power and Intelligent Systems Laboratory Electrical and Computer Engineering Department University of Missouri Rolla MO USA

A new approach to identify the nonlinear model of an induction machine using two generalized neurons (GNs) is presented in this paper. Compared to the multilayer perceptron feedforward neural network, a GN has simpler structure and lesser requirement in terms of memory storage which is makes it attractive for hardware implementation. This method shows that with less number of weights, GN is able to learn the dynamics of an induction machine. The proposed model is made by two coupled networks. A modified particle swarm optimization algorithm is designed to solve this distinctive GN training problem. A pseudo-random binary sequence signal injected to the induction machine operating at its rated value was chosen as the test input signal. For validation, the trained GN model is applied on the different operating conditions of the system.

关键词： Induction machines Stators Neurons Multilayer perceptrons Neural networks Multi-layer neural network Feedforward neural networks Neural network hardware Particle swarm optimization Algorithm design and analysis

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