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 ...
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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
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 result...
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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
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 p...
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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
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 fro...
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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.
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 in...
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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.
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 provide...
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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 achie...
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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 MOE...
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Prompted by the increasing demands in system reliability and availability, fault diagnosis and accommodation has quickly become one of the most active research areas in the intelligentcontrol community. Yet, the onli...
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Prompted by the increasing demands in system reliability and availability, fault diagnosis and accommodation has quickly become one of the most active research areas in the intelligentcontrol community. Yet, the online fault accommodation controls for the system under catastrophic failures that result in drastic changes and/or changing of dynamic structure are still unsolved. In this work, a sufficient condition for system online stability with changes of dynamic structure under catastrophic failures has been derived based upon discrete-time Lyapunov stability theory. The theoretical analysis indicates that the online control problem can be solved without complete realization of the system dynamics given satisfaction of specific assumptions. An online fault accommodation control framework is proposed to deal with the desired trajectory-tracking problem for systems suffering from various abrupt and unanticipated catastrophic failures. Once a fault is detected, an artificial neural network is suggested as the online estimator to approximate the most recent behaviour of the unknown system failure dynamics. Effective control signals to accommodate the dynamic failures are then computed through the realization of the estimator for the unknown failures based only upon the partially available information of the faults. Extensive simulation studies have been completed to validate the proposed online control architecture under various multiple failures, noisy environments, and false alarm scenarios. The simulations show encouraging results and demonstrate the effectiveness of the proposed control methodology for unanticipated and unknown time-varying failures in online situations based solely upon insufficient information about the system dynamics.
A Mamdani based fuzzy logic controller is designed and implemented for controlling a STATCOM, which is connected to a 10 bus multimachine power system. Such a controller does not need any prior knowledge of the plant ...
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