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AN OPTIMISATION-BASED APPROACH FOR DESIGNING INDIRECT SENSORS APPLIED TO AN INDUCTION MOTOR
Valdés-González,Gonzalo; Valdés-González,Héctor; Zolezzi,Juan;
Revista Facultad de Ingeniería - Universidad de Tarapacá , 2006, DOI: 10.4067/S0718-13372006000100011
Abstract: this article proposes an innovative strategy to the problem of non-linear estimation of states in an induction motor, (im). this method allows the estimation of variables that are difficult to access or that are simply impossible to measure. the estimation is made possible by using indirect measures, through the consideration of a dynamic model of the process and an estimation algorithm based on non-linear optimization. this state estimation strategy (a.k.a. moving horizon state estimation or mhse) in an im allows the determination of the flux magnitude and the velocity or position of the rotor. its principal advantages are the simplicity of its implementation, good convergence characteristics, independence from pre-established model structures, and easy tuning. simulated results corroborate the effectiveness of the proposed method through estimates of the velocity of an im under different operational situations
AN OPTIMISATION-BASED APPROACH FOR DESIGNING INDIRECT SENSORS APPLIED TO AN INDUCTION MOTOR MéTODO DE ESTIMACIóN DE ESTADOS BASADO EN OPTIMIZACIóN APLICADO A UN MOTOR DE INDUCCIóN
Gonzalo Valdés-González,Héctor Valdés-González,Juan Zolezzi
Revista Facultad de Ingeniería - Universidad de Tarapacá , 2006,
Abstract: This article proposes an innovative strategy to the problem of non-linear estimation of states in an induction motor, (IM). This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. The estimation is made possible by using indirect measures, through the consideration of a dynamic model of the process and an estimation algorithm based on non-linear optimization. This state estimation strategy (a.k.a. Moving Horizon State Estimation or MHSE) in an IM allows the determination of the flux magnitude and the velocity or position of the rotor. Its principal advantages are the simplicity of its implementation, good convergence characteristics, independence from pre-established model structures, and easy tuning. Simulated results corroborate the effectiveness of the proposed method through estimates of the velocity of an IM under different operational situations Este artículo propone una novedosa estrategia aplicada al problema de estimación no lineal de estados en un motor de inducción (MI). Este método permite, en general, la estimación de variables de difícil acceso o que simplemente no se pueden medir. Lo cual es posible a través de mediciones indirectas, considerando un modelo dinámico del proceso y un algoritmo de estimación basado en optimización no lineal. El principal atractivo de esta estrategia de estimación de estados denominada MHSE (Moving Horizon State Estimation) en un MI, que permite conocer la magnitud del flujo, la velocidad o posición del rotor, es su simplicidad de implementación, sus buenas características de convergencia, su independencia de estructuras preestablecidas de modelos y su fácil sintonía. Resultados en simulación muestran la efectividad del método propuesto efectuando la estimación de la velocidad de un MI bajo diferentes puntos de operación
Spatial and Temporal Variation of Stable Isotopes in Precipitation across Costa Rica: An Analysis of Historic GNIP Records  [PDF]
Ricardo Sánchez-Murillo, Germain Esquivel-Hernández, Kristen Welsh, Erin S. Brooks, Jan Boll, Rosa Alfaro-Solís, Juan Valdés-González
Open Journal of Modern Hydrology (OJMH) , 2013, DOI: 10.4236/ojmh.2013.34027
Abstract: The location of Costa Rica on the Central American Isthmus creates unique microclimate systems that receive moisture inputs directly from the Caribbean Sea and the Pacific Ocean. In Costa Rica, stable isotope monitoring was conducted by the International Atomic Energy Agency and the World Meteorological Association as part of the worldwide effort entitled Global Network of Isotopes in Precipitation. Sampling campaigns were mainly comprised of monthly-integrated samples during intermittent years from 1990 to 2005. The main goal of this study was to determine spatial and temporal isotopic variations of meteoric waters in Costa Rica using historic records. Samples were grouped in four main regions: Nicoya Peninsula (d2H = 6.65d18O0.13; r2 = 0.86); Pacific Coast (d2H = 7.60d18O + 7.95; r2 = 0.99); Caribbean Slope (d2H = 6.97d18O + 4.97; r2 = 0.97); and Central Valley (d2H = 7.94d18O + 10.38; r2 = 0.98). The water meteoric line for Costa Rica can be defined as d2H = 7.61d18O + 7.40 (r2
Near Surface Carbon Dioxide and Methane in Urban Areas of Costa Rica  [PDF]
Germain Esquivel-Hernández, Mario Villalobos-Forbes, Ricardo Sánchez-Murillo, Christian Birkel, Juan Valdés-González, Jan Boll
Open Journal of Air Pollution (OJAP) , 2015, DOI: 10.4236/ojap.2015.44018
Abstract: Little information is available for Central America regarding methane and carbon dioxide mixing ratios in urban areas. This work reports a representative spatial and seasonal study of near surface carbon dioxide and methane, carried out between July 2014 and January 2015 (27 weeks) in the Central Valley of Costa Rica, and other urban and rural sites across the country and covering three distinct seasons: Mid-summer drought (July-August), wet season (September-November) and transition period (December-January). The mixing ratios of both gases are clearly influenced by the metropolitan area, and by the prevailing atmospheric conditions during the wet season months. Average carbon dioxide concentration (629 ± 80 ppm) and average methane concentration (2192 ± 110 ppb) were up to 8% and up to 10%, respectively, higher during the wet season than the values recorded outside this period. HYSPLIT back air mass trajectories analysis, and weather data available for the Central Valley, suggest that these differences arise as result of a reduction in the mixing layer of depth (~425 m) and the wind speed (~1.5 m/s) across the valley, favoring the accumulation of polluted air masses in the metropolitan area. Other natural and anthropogenic sources, like the volcanic emissions of the Turrialba Volcano and the livestock activities at rural sites, apparently influence the mixing ratios of both gases across Costa Rica. Although the scope of this study is limited to representative seasonal conditions of the Central Valley in 2014 and 2015, it is possible considering the information presented in this work that the “dome” phenomenon can be assumed to exist.
Optimización Global por Intervalos: Aplicación a Problemas con Parámetros Inciertos
Campos,Pedro G; Valdés-González,Héctor M;
Información tecnológica , 2006, DOI: 10.4067/S0718-07642006000500011
Abstract: this paper presents the application of a software platform to the problem of global optimization of non linear criteria with restrictions by interval analysis. the problem has been tackled by representing the variables and uncertain parameters of the criterion to be optimized as intervals. the mathematics of the intervals used and the optimization algorithm, together with their role in a larger application, are described. results for differentiable and non-differentiable problems are shown and contrasted with another software for global optimization to highlight the benefits of the implemented platform.
MéTODOS DE ESTIMACIóN NO LINEAL APLICADOS AL PROBLEMA DE EXPECTATIVAS DE INFLACIóN
Arriagada-Benítez,Mauricio; Valdés-González,Héctor; Pedraja-Rejas,Liliana;
Ingeniare. Revista chilena de ingeniería , 2009, DOI: 10.4067/S0718-33052009000300014
Abstract: this work describes and analyses the extended kalman filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. an estimation of the exante inflation for a preestablished data set is carried out. this is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. from the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.
DETECCIóN DE PéRDIDAS EN TUBERíAS DE AGUA: PROPUESTA BASADA EN UN BANCO DE FILTROS
Castro Burgos,Lucía; Valdés-González,Héctor;
Ingeniare. Revista chilena de ingeniería , 2009, DOI: 10.4067/S0718-33052009000300011
Abstract: currently leak detection (ld) in water pipelines is an active area of research that is attracting increasing interest due to the importance of the safe transport of this vital resource. this work considers the problem of ld in water pipes by means of analytical redundancy, based on a mathematical model and using state estimation techniques. the main aim of this work is to research, propose, implement and apply efficient algorithms that allow to tackle generally the ld. to achieve this, a bank of filters including kalman filters (kf) and particle filter (pf) is proposed and evaluated. thus a conceptual contribution to the formulation of the ld problem is proposed in a modular way so that future studies of other techniques can solve the problem. in addition, efficient and reliable algorithms are developed, based on a state estimator capable of responding to industrial standards such as the delivery, from input and output measures available, of a reliable estimate of the state of the process and that is independent of the linear or non-linear dynamics and easy to handle and configure. the computer simulation and the experimental results show the effectiveness of combining kf with pf for the simple case of two sequential leaks in a pipe, presenting advantages such as rapid convergence and reducing the estimation error which are important factors in ld in water pipeline.
Optimización Global por Intervalos: Aplicación a Problemas con Parámetros Inciertos Global Optimization by Interval Analysis: Application to Problems with Uncertain Parameters
Pedro G Campos,Héctor M Valdés-González
Información Tecnológica , 2006,
Abstract: Este artículo presenta la aplicación de una plataforma de software, que permite realizar optimización global de criterios no lineales con restricciones utilizando análisis por intervalos. El problema ha sido abordado considerando las variables del criterio a optimizar como intervalos, así como también los parámetros con incertidumbre. Se describe la aritmética por intervalos utilizada, el algoritmo de optimización implementado y su utilización como parte de una aplicación mayor que requiere de optimización. Se presentan resultados para problemas de criterios diferenciables y no diferenciables, contrastados con otro software de optimización global, que muestran las bondades de la plataforma implementada. This paper presents the application of a software platform to the problem of global optimization of non linear criteria with restrictions by interval analysis. The problem has been tackled by representing the variables and uncertain parameters of the criterion to be optimized as intervals. The mathematics of the intervals used and the optimization algorithm, together with their role in a larger application, are described. Results for differentiable and non-differentiable problems are shown and contrasted with another software for global optimization to highlight the benefits of the implemented platform.
MéTODOS DE ESTIMACIóN NO LINEAL APLICADOS AL PROBLEMA DE EXPECTATIVAS DE INFLACIóN NONLINEAR ESTIMATION METHODS APPLIED TO A PROBLEM OF EXPECTED INFLATION
Mauricio Arriagada-Benítez,Héctor Valdés-González,Liliana Pedraja-Rejas
Ingeniare : Revista Chilena de Ingeniería , 2009,
Abstract: En este trabajo se describe y analiza, luego de tener la ecuación que relaciona la dinámica de las expectativas de la tasa de interés real y de la inflación, el filtro extendido de Kalman. Asimismo, se realiza la estimación de la inflación exante para una serie de datos preestablecida. Se efectúa una comparación con el método de estimación de horizonte móvil utilizado en situaciones cuando producto de las incertidumbres paramétricas del modelo éste se torna no lineal. La aplicación de estos métodos a datos reales permite concluir que las estimaciones efectuadas a través del método de horizonte móvil, combinado a un algoritmo heurístico de optimización logran los mejores resultados. This work describes and analyses the Extended Kalman Filter with regard to an equation that relates the dynamic of the expected real interest rates and inflation. An estimation of the exante inflation for a preestablished data set is carried out. This is compared with the same calculation using a moving horizon estimation method for situations that are non lineal due to parametric uncertainties of the model. From the application of these methods to real data, it can be concluded that the estimations based on the moving horizon method, combined with a heuristic optimization algorithm, yield better results.
DETECCIóN DE PéRDIDAS EN TUBERíAS DE AGUA: PROPUESTA BASADA EN UN BANCO DE FILTROS LEAK DETECTION IN WATER PIPELINES: PROPOSAL BASED ON A BANK OF FILTERS
Lucía Castro Burgos,Héctor Valdés-González
Ingeniare : Revista Chilena de Ingeniería , 2009,
Abstract: Actualmente la detección de pérdidas (DP) en tuberías de agua es un área de investigación activa, y con un creciente interés, debido a la importancia del transporte seguro del vital elemento. Este trabajo considera el problema de DP en tuberías de agua por medio de redundancia analítica, basada en un modelo matemático y utilizando técnicas de estimación de estados, teniendo por objetivo principal estudiar, proponer, implementar y aplicar algoritmos eficientes que permitan abordar de manera general el problema de DP. Para lograr esto se propone y evalúa un banco de filtros, implementados con filtros de Kalman (FK) y filtros de partículas (FP). Con esto se busca contribuir conceptualmente a la formulación del problema de DP, de manera modular, permitiendo que en un estudio futuro otras técnicas puedan ser utilizadas para resolver el problema. Además, obtener algoritmos eficientes y confiables, basados en un estimador de estados capaces de responder a requerimientos industriales, tales como: entregar, a partir de medidas de entrada y salida disponibles, una estimación fiable del estado del proceso, esto con independencia de la dinámica lineal o no lineal, asimismo, ser de fácil manejo y fácil configuración. La simulación computacional y los resultados experimentales muestran la efectividad de combinar FP con FK, para el caso básico de dos pérdidas secuenciales en una tubería, presentando ventajas de rápida convergencia y reducción del error de estimación, factores importantes en el problema de DP en ductos hídricos. Currently leak detection (LD) in water pipelines is an active area of research that is attracting increasing interest due to the importance of the safe transport of this vital resource. This work considers the problem of LD in water pipes by means of analytical redundancy, based on a mathematical model and using state estimation techniques. The main aim of this work is to research, propose, implement and apply efficient algorithms that allow to tackle generally the LD. To achieve this, a bank of filters including Kalman Filters (KF) and Particle Filter (PF) is proposed and evaluated. Thus a conceptual contribution to the formulation of the LD problem is proposed in a modular way so that future studies of other techniques can solve the problem. In addition, efficient and reliable algorithms are developed, based on a state estimator capable of responding to industrial standards such as the delivery, from input and output measures available, of a reliable estimate of the state of the process and that is independent of the linear or non-linear dyna
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