In this paper a Wells turbine control is presented. For this purpose, a control scheme for the flow coefficient is derived based on the addition of external resistances in series with the rotor winding of the inductio...
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ISBN:
(纸本)9781424442515
In this paper a Wells turbine control is presented. For this purpose, a control scheme for the flow coefficient is derived based on the addition of external resistances in series with the rotor winding of the induction generator connected to the turbine. Due to the stalling behaviour, the generator increases its velocity as the flow coefficient of the turbine approaches the critical point at which the turbine losses power. The proposed control system does appropriately adapt the rotor resistance according to the entry pressure drop. To do so, the control implements a continuous resistance switching depending on the pressure drop and it will be demonstrated that the average power of the turbine and generator are significantly higher in the controlled case than in the uncontrolled one. It is stated that there exist an optimal value of external resistances for each specific range of pressure drop and it is verified that greater input pressure drop does not imply higher power output unless the stalling behaviour is avoided.
Abstract Nuclear fusion has the potential to produce unlimited, clean energy, which presents itself as a reliable energy supply but it also helps to stop the threat of climate change that faces the world nowadays. How...
Abstract Nuclear fusion has the potential to produce unlimited, clean energy, which presents itself as a reliable energy supply but it also helps to stop the threat of climate change that faces the world nowadays. However, to sustain the pulse duration long enough to produce the necessary energy, new controls have to be developed, composing a new application area of controlengineering, with new and interesting challenges for the control community. In this sense, this paper deals with the modeling of tokamak nuclear fusion reactors. In order to control the creation of unstable modes in fusion processes, it is necessary to derive numerical models suitable for control strategies. The model presented in this paper addresses flux and energy conservation issues, discussing the mechanisms behind the creation of uncontrollable modes. The dynamics of the system is given by means of the energy functions which are solved for the currents in the structure, plasma current and plasma position. Thus, the equations for the state variables are derived based on the Hamiltonian equation of motion. In order to solve this system numerically, this model is linearized around an operation point by taking a Newton-Raphson step. Besides, the system output is completed by considering the equations for the flux and the poloidal field. Finally, the resulting low-order linear model is modified so as to obtain the corresponding state-space model which is verified by means of numerical experiments.
Gaussian mixture model (GMM)-based vector quantization of line spectral frequencies (LSFs) has gained wide acceptance in speech coding. In predictive coding of LSFs, the GMM approach utilizing Kalman filtering princip...
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Gaussian mixture model (GMM)-based vector quantization of line spectral frequencies (LSFs) has gained wide acceptance in speech coding. In predictive coding of LSFs, the GMM approach utilizing Kalman filtering principles to account for quantization noise has been shown to perform better than a baseline GMM recursive coder approaches for both clean and packet loss conditions at roughly the same complexity. However, the GMM Kalman based predictive coder was not specifically designed for operation in packet loss conditions. In this paper, we show how an initial GMM Kalman predictive coder can be utilized to obtain a robust GMM predictive coder specifically designed to operate in packet loss. In particular, we demonstrate how one can define sets of encoding and decoding modes, and design special Kalman encoding and decoding gains for each set. With this framework, GMM predictive coding design can be viewed as determining the special Kalman gains that minimize the expected minimum mean squared error at the decoder in packet loss conditions. The simulation results demonstrate that the proposed robust Kalman predictive coder achieves better performance than the baseline GMM predictive coders.
This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured ima...
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This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured images to feed the trajectory, which drives the UAV towards the next point to take the next shot, until the identification is completed. The multiple patterns of the input image make the problem difficult. Our approach orders the points of the image to identify the existent edges, and computes the trajectory as a minimization problem using a multi-objective function that gathers information about the boundary and the polynomial that fit in these edges.
This paper presents a text localization approach for binarized printed document images. Emphasis is given to the feature extraction and feature selection stages. In the former, several document structure elements and ...
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In harsh industrial environment, industrial wireless networks need high quality performance at real-time, deterministic schedule, reliability and low-power consumption, and so on, or it will bring disastrous consequen...
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The deployment of wireless technologies for device communication in the industrial control field is a challenging and promising issue mainly due to the increasing flexibility and the mobility. However, with limited re...
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In video-based surveillance people monitor a wide spatial area through video sensors for anomalous events related to safety and security. The size of the area, the number of video sensors, and the camera's narrow ...
In video-based surveillance people monitor a wide spatial area through video sensors for anomalous events related to safety and security. The size of the area, the number of video sensors, and the camera's narrow field-of-view make this a challenging cognitive task. computer vision researchers have developed a wide range of algorithms to recognize patterns in the video stream (intelligent cameras). These advances create a challenge for human supervision of these intelligent surveillance camera networks. This paper presents a new visualization that has been developed and implemented to integrate video-based computer vision algorithms with control of pan-tilt-zoom cameras in a manner that supports the human supervisory role.
We present an automatic query expansion approach by generalizing the vector space model of information retrieval. In this framework, the images are presented by vectors of weighted concepts similar to the keyword-base...
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ISBN:
(纸本)9781605584805
We present an automatic query expansion approach by generalizing the vector space model of information retrieval. In this framework, the images are presented by vectors of weighted concepts similar to the keyword-based representation in the text retrieval domain. The concepts comprise of color and texture patches from local image regions in a multi-dimensional feature space. To generate the concept vocabularies and represent the images, statistical model is built by utilizing a multi-class Support Vector Machine (SVM)-based classification technique. For automatic query expansion, the correlations between concepts are analyzed based on the neighborhood proximity between the concepts in encoded images by considering the local feedback information. The experimental results on a photographic image collection demonstrate the effectiveness of the proposed query expansion approaches. Copyright 2009 ACM.
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