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检索条件"机构=Robotics and Intelligent Systems Laboratory Electrical and Computer Engineering"

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Hybrid Model of WT and ANFIS and Its Application on Time Series Prediction of Ship Roll Motion

Hybrid Model of WT and ANFIS and Its Application on Time Ser...

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Computational engineering in systems Applications, CESA, IMACS Multiconference on FLAGGED

作者： Hui Li Chen Guo Simon X. Yang Hongzhang Jin Automation and Electrical Engineering College Dalian Maritime University Dalian China Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph Canada Automation College Harbin Engineering of Technology Harbin China

Based on the multi time and frequency scale and the nonlinear character of ship roll motion, a hybrid model prediction approach combining wavelet transform (WT) and adaptive neuro-fuzzy inference system (ANFIS) is proposed in this paper. By using multi-resolution nalysis (MRA) of WT, multilevel 1-D wavelet decompositions of roll motion are completed to obtain simple and regular period signals. Then the multiple-input/single-output (MISO) ANFIS model is employed as prediction model for the main decomposed signals above. Finally, a prediction result is given through linear combination. The simulation experiments demonstrate the proposed method can effectively reduce the prediction difficulty and obtain better prediction precision. This method can also be used in ship pitch and heave motion prediction

关键词： Predictive models Marine vehicles Wavelet analysis Wavelet transforms Multiresolution analysis Wavelet domain robotics and automation Educational institutions intelligent robots Frequency

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Fuzzy reinforcement learning for embedded soccer agents in a multi-agent context

Fuzzy reinforcement learning for embedded soccer agents in a...

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作者： Tehrani, A.M. Kamel, M.S. Khamis, A.M. Pattern Analysis and Machine Intelligence Lab. Electrical and Computer Engineering Department University of Waterloo Waterloo Ont. N2L 3G1 Canada Mechanical Engineering Department University of Waterloo Canada Department of Cooperative Intelligent Systems Canada Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Canada Department of Systems Engineering and Automation Carlos III University of Madrid Spain

The work presented in this paper aims at combining fuzzy function approximation and reinforcement learning in order to create robotic soccer agents that are able to coordinate their behaviours locally and socially while learning from experience. This simultaneous coordination and learning ability can play a crucial role in improving the behaviour usage of robotic soccer agents. To achieve this goal, a fuzzy reinforcement learning technique for a single agent is first examined and then this technique is applied to multiple agents. The conducted experiments through a soccer simulation system show that the performance of robot scoring speed is improved using the proposed approach.

关键词： Multi agent systems

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Asynchronous event-based communication across Service Brokers 12

Asynchronous event-based communication across Service Broker...

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12th European Wireless Conference on Enabling Technologies for Wireless Multimedia Communications, European Wireless 2006

作者： Koutsoloukas, E. Kapellaki, S. Prezerakos, G.N. Tselikas, N. Venieris, I.S. Kaklamani, D.I. Intelligent Communications and Broadband Networks Laboratory School of Electrical and Computer Engineering National Technical University of Athens 9 Heroon Polytechneioy str. Zografou Athens Greece Technological Education Institute of Piraeus Faculty of Technology Dpt of Electronic Computing Systems Petrou Ralli and Thivon 250 Athens12244 Greece

ISBN: (纸本)9783800729616

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 Iifecycle. 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： Web services

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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...

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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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Particle Swarm Optimization based Defensive Islanding of Large Scale Power System

Particle Swarm Optimization based Defensive Islanding of Lar...

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International Joint Conference on Neural Networks (IJCNN)

作者： Wenxin Liu D.A. Cartes G.K. Venayagamoorthy Center of Advanced Power Systems (CAPS) Florida State University Tallahassee USA Real-Time Power and Intelligent Systems Laboratory the Department of Electrical and Computer Engineering University of Missouri MO USA

Defensive islanding is an efficient way to avoid catastrophic failures and wide area blackouts. Power system splitting especially for large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution (if one exists) for large scale power system in real time. This paper proposes to utilize the computational efficiency property of binary particle swarm optimization (BPSO) to find some efficient splitting solutions in limited timeframe. The solutions are optimized based on a cost function considering the balance between real power generation and consumption, the relative importance of customers, the capacities of distribution and transmission systems, and possibility of region to be impacted, etc. The solutions not only provide the lines to cut but also the corresponding load shedding information in each island. Simulations with large scale power system demonstrate the effectiveness of the proposed algorithm.

关键词： Particle swarm optimization Large-scale systems Power systems Power system stability Power system protection Power system dynamics Cost function Power system simulation Real time systems Power system faults

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Simulation model for assessing transient performance of capacitive voltage transformers

Simulation model for assessing transient performance of capa...

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IEEE General Meeting Power& Energy Society

作者： I. Sule U.O. Aliyu G.K. Venayagamoorthy Electrical and Electronics Engineering Department Federal Polytechnic Mubi Nigeria Electrical Engineering Programme Abubakar Tafawa Balewa University Bauchi Nigeria Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

In determining the correct operation of relays of a protection scheme, proper representation of instrument transformers and their behavior in conditions where there can be transient is very critical. This paper presents a simulation model for assessing the transient performance of capacitive voltage transformers (CVTs). In order to test the validity of the developed model, four CVT operational conditions are considered using field data collected from one of the Nigerian electric utility 330/132/33 kV substations. The model simulation results revealed various configuration performance responses that could affect relay protection schemes to different degrees. As expected, the CVT responses showed that faults initiated at zero voltage crossing, which is the worst transient condition, produced transient voltage magnitude up to 40% of the nominal voltage while faults initiated at the crest produced minimum transient voltage magnitude. It is shown that the model developed for the selected instrument transformer yielded satisfactory results

关键词： Voltage transformers Mathematical model Power system transients Instrument transformers Power system protection Protective relaying Power system relaying Power system reliability Substations MATLAB

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Bacteria Foraging: A New Tool for Simultaneous Robust Design of UPFC Controllers

Bacteria Foraging: A New Tool for Simultaneous Robust Design...

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International Joint Conference on Neural Networks (IJCNN)

作者： M. Tripathy S. Mishra G.K. Venayagamoorthy University College of Engineering Burla Orissa India Department of Electrical Engineering Indian Institute of Technology New Delhi India Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory University of Missouri MO USA

Robust tuning of lead-lag type controller used for regulating FACTS control signal to improve dynamic stability has been an area of interest in research. This paper presents a new approach based on the foraging behavior of *** Bacteria in the human intestine, to optimize simultaneously three constants each of four lead-lag type UPFC controller present in a single machine infinite bus (SMIB) power system. For the tuning purpose, a multi-objective cost function is formulated that accounts for damping factors and ratios of various system modes for a wide range of operating conditions. Robustness of the proposed tuning method is shown by transient stability analysis of the system time domain simulations when subjected to disturbances at different operating conditions.

关键词： Microorganisms Robust control Robust stability Power system dynamics Power system stability Power system simulation Power system transients Humans Intestines Control systems

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Recurrent Neural Network Based Predictions of Elephant Migration in a South African Game Reserve

Recurrent Neural Network Based Predictions of Elephant Migra...

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International Joint Conference on Neural Networks (IJCNN)

作者： P. Palangpour G.K. Venayagamoorthy K. Duffy Real-Time Power and Intelligent Systems (RTPIS) Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA Centre for Systems Research Durban Institute of Technology Durban South Africa

A large portion of South Africa's elephant population can be found on small wildlife reserves. When confined to enclosed reserves the elephant densities are much higher than observed in the wild. The large nutritional demands and destructive foraging behavior of elephants threaten rare species of vegetation. If conservation management is to protect threatened species of vegetation, knowing how long elephants will stay in one area of the reserve as well as which area they will move to next is essential. The goal of this study is to train a recurrent neural network (RNN) to continuously predict an elephant herd's next position in the Pongola Game Reserve. Accurate predictions would provide a useful tool in assessing future impact of elephant populations on different areas of the reserve. The particle swarm optimization (PSO) algorithm is used to adapt the weights of the neural network. Results are presented to show the effectiveness of RNN-PSO for elephant migration prediction.

关键词： Recurrent neural networks intelligent networks Vegetation Neural networks Africa Wildlife Particle swarm optimization Power system management Predictive models Protection

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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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