Results 201 to 210 of about 9,506 (241)
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Excitation control in a synchronous machine via an artificial neural network
Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 2002This paper presents an application of artificial neural networks (ANN) as a controller for a synchronous machine excitation system. A hierarchical architecture of an ANN is adopted for the controller design, which is used for data mapping and control respectively, based on the backpropagation algorithm (BPA). The controller's operation does not require
null Weiminn Zhang, M.E. El-Hawary
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Synchronous machine steady-state stability analysis using an artificial neural network
IEEE Transactions on Energy Conversion, 1991In the developed artificial neural network, those system variables which play an important role in steady-state stability, such as generator outputs and power system stabilizer parameters, are used as the inputs. The output of the neural net provides the information on steady-state stability.
Chen, C. R., Hsu, Yuan-Yih
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Artificial Neural Network Based Automatic Voltage Regulator for a Stand-Alone Synchronous Generator
2019 8th International Conference on Renewable Energy Research and Applications (ICRERA), 2019In this study, an automatic voltage regulator (AVR) based on artificial neural network (ANN) is presented for a standalone synchronous generator. The AVR maintains the constant output voltage independent of load by altering its excitation current and brings the output voltage to the desired level.
BAL, GÜNGÖR +2 more
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AN ARTIFICIAL NEURAL NETWORK COORDINATED EXCITATION/GOVERNOR CONTROLLER FOR SYNCHRONOUS GENERATORS
Electric Machines & Power Systems, 1997ABSTRACT The paper presents a novel coordinated excitation/governor artificial neural network (ANN) based controller for AC synchronous generators. The proposed ANN based controller replaces the full global action of the voltage regulator, power system stabilizer and speed governor controls.
A. M. SHARAF, TJING T. LIE
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Improving Synchronous Generator's differential protection with the use of Artificial Neural Networks
2012 IEEE Power and Energy Society General Meeting, 2012This paper presents an alternative technique to detect and correct waveforms distortion due to Current Transformer (CT) saturation using intelligent tools based on Artificial Neural Network (ANN). The Real-time Digital Simulator (RTDS) was used to evaluate the performance of the ANNs running in a real-time embedded system.
Renato Machado Monaro +3 more
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Expert Systems with Applications, 2011
This paper presents an artificial neural network approach for locating internal faults in salient-pole synchronous generator. This method uses samples of magnetic flux linkages to reach a decision. Meyer wavelet probabilistic neural network (MWPNN) as main part of this fault diagnosis method is utilized to detect internal faults.
Hamid Yaghobi +2 more
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This paper presents an artificial neural network approach for locating internal faults in salient-pole synchronous generator. This method uses samples of magnetic flux linkages to reach a decision. Meyer wavelet probabilistic neural network (MWPNN) as main part of this fault diagnosis method is utilized to detect internal faults.
Hamid Yaghobi +2 more
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Tension Identification of Multi-motor Synchronous System Based on Artificial Neural Network
2007Sensorlesstension control of multi-motor synchronous system with closed tension loop is required in many fields. How to identify the knowledge of instantaneous magnitude of tension is key. In this paper the tension identification is managed on the base of stator currents and its previous values with neural network.
Guohai Liu +4 more
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2012 11th International Conference on Machine Learning and Applications, 2012
In the classic ANN-based approaches, the synchronous motor parameters mostly could be modeled with n-hidden layered networks. It is an important challenge in driver software development is to realize complex mathematical models in real time environments and circuits.
Ramazan Bayindir +3 more
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In the classic ANN-based approaches, the synchronous motor parameters mostly could be modeled with n-hidden layered networks. It is an important challenge in driver software development is to realize complex mathematical models in real time environments and circuits.
Ramazan Bayindir +3 more
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Synchronous learning versus asynchronous learning in artificial neural networks
IEEE International Conference on Systems Engineering, 1991Conditions of configuring feedforward neural networks without local minima are analyzed for both synchronous and asynchronous learning rules. Based on the analysis, a learning algorithm that integrates a synchronous-asynchronous learning rule with a dynamic configuration rule to train feedforward neural networks is presented. The theoretic analysis and
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Analysis of controlled permanent magnet synchronous motor using artificial neural network
ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501), 2002This paper presents a modern approach of speed control for permanent magnet synchronous motors (PMSM) using on-line artificial neural network (ANN) techniques. The overall system will be simulated under various operating conditions. The use of ANN as a controller makes the drive robust with faster dynamic response, higher accuracy and insensitive to ...
K.I. Saleh +3 more
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