Controlador Neuro-Robusto Para Sistemas No Lineales

Rolle, José Luis Calvo; Machón-González, Iván; Garcı́a, Hilario López

doi:10.6036/3949

Cited by 25 publications

(6 citation statements)

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“…In other investigations, new intelligent techniques are developed to ensure a right system operation [17,33]. Some studies are focused on the development of a hybrid controller combining classical and intelligent techniques; a Neuro-PID controller is designed in [10]. Other papers design a new type of controller like the one explained in [12], an adaptive inverse controller using an online learning algorithm for neural networks.…”

Section: Intelligent Systemsmentioning

confidence: 99%

“…Other papers design a new type of controller like the one explained in [12], an adaptive inverse controller using an online learning algorithm for neural networks. The fields of application for these intelligent systems are very different; for example, [11] explains the use of a hybrid controller to improve the performance of a steel rolling control process. Intelligent algorithms are used to implement a tracking of objects function for a robot in [42].…”

Section: Intelligent Systemsmentioning

confidence: 99%

“…Among the different criteria employed for Discriminant Analysis, the Fisher's Discriminant Criterion [5], tested on this work, has better results than others. When linear classification is possible, it is important to emphasize that good results are obtained with this technique [36,11]. When FLDA technique is employed, the training data is used to obtain hyper planes with the aim of separating the classes.…”

Section: Fisher's Linear Discriminant Analysis (Flda)mentioning

confidence: 99%

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An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger

Casteleiro‐Roca

Quintián

Calvo-Rolle

et al. 2016

Journal of Applied Logic

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The heat pump with geothermal exchanger is one of the best methods to heat up a building. The heat exchanger is an element with high probability of failure due to the fact that it is an outside construction and also due to its size. In the present study, a novel intelligent system was designed to detect faults on this type of heating equipment. The novel approach has been successfully empirically tested under a real dataset obtained during measurements of one year. It was based on classification techniques with the aim of detecting failures in real time. Then, the model was validated and verified over the building; it obtained good results in all the operating conditions ranges.

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Section: Intelligent Systemsmentioning

confidence: 99%

Section: Intelligent Systemsmentioning

confidence: 99%

Section: Fisher's Linear Discriminant Analysis (Flda)mentioning

confidence: 99%

See 1 more Smart Citation

An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger

Casteleiro‐Roca

Quintián

Calvo-Rolle

et al. 2016

Journal of Applied Logic

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“…El modelo que se propone es un modelo híbrido inteligente, aplicando inicialmente técnicas de agrupamiento como paso previo a la regresión propiamente dicha. Concretamente, se utilizará un modelo híbrido basado en redes neuronales artificiales (ANN) (García et al, 2013;Calvo-Rolle et al, 2013;García et al, 2014;Quintián et al, 2014;Quintian Pardo et al, 2012) ya queéstas permiten obtener un modelo relativamente simple para recrear con precisión sistemas no lineales (Alaiz Moretón et al, 2011;Rolle et al, 2011).…”

Section: Introductionunclassified

Sistema híbrido inteligente para la predicción de la tensión de una pila de combustible basada en hidrógeno

Casteleiro‐Roca

Barragán

Segura

et al. 2019

Rev. iberoam. autom. inform. ind.

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<p>Por razones de sostenibilidad y estrategia energética, entre otras, existe en la actualidad una tendencia clara hacia el uso de nuevas formas de obtención, almacenamiento y gestión de energía, más eficientes y con un carácter eminentemente sostenible. Con este fin, se está investigando sobre sistemas de almacenamiento de energía; de los que uno de los más prometedores, en lo que a capacidad y movilidad se refiere, es el basado en hidrógeno. En el presente trabajo se obtiene un modelo para predecir el comportamiento dinámico de una pila de combustible alimentada por hidrógeno, lo cual permitirá mejorar su control entre otras aplicaciones. Las variables usadas en esta investigación se han extraído de un banco de pruebas real, donde se monitoriza una pila de combustible mientras se producen variaciones en una carga programable conectada a la salida de la misma. Para realizar este modelado se opta por estudiar la implementación de un modelo híbrido basado en técnicas de agrupamiento y, posteriormente, técnicas inteligentes de regresión con redes neuronales artificiales sobre cada uno de los grupos. La propuesta se ha probado con dos conjuntos de datos de validación, consiguiendo resultados altamente satisfactorios.</p>

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“…The hybrid system presented in this paper uses Artificial Neural Networks and Polynomial Regression techniques to perform the regression phase [47][48][49][50][51][52]. This type of hybrid model allows for obtaining good accuracy in nonlinear systems [53][54][55][56][57][58].…”

Section: Introductionmentioning

confidence: 99%

Fuel Cell Hybrid Model for Predicting Hydrogen Inflow through Energy Demand

et al. 2019

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Hydrogen-based energy storage and generation is an increasingly used technology, especially in renewable systems because they are non-polluting devices. Fuel cells are complex nonlinear systems, so a good model is required to establish efficient control strategies. This paper presents a hybrid model to predict the variation of H2 flow of a hydrogen fuel cell. This model combining clusters’ techniques to get multiple Artificial Neural Networks models whose results are merged by Polynomial Regression algorithms to obtain a more accurate estimate. The model proposed in this article use the power generated by the fuel cell, the hydrogen inlet flow, and the desired power variation, to predict the necessary variation of the hydrogen flow that allows the stack to reach the desired working point. The proposed algorithm has been tested on a real proton exchange membrane fuel cell, and the results show a great precision of the model, so that it can be very useful to improve the efficiency of the fuel cell system.

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Controlador Neuro-Robusto Para Sistemas No Lineales

Cited by 25 publications

References 0 publications

An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger

An intelligent fault detection system for a heat pump installation based on a geothermal heat exchanger

Sistema híbrido inteligente para la predicción de la tensión de una pila de combustible basada en hidrógeno

Fuel Cell Hybrid Model for Predicting Hydrogen Inflow through Energy Demand

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