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Control Neurodifuso de Humedad para un Fitotrón

Authors: CARLOS ALFREDO RAZO MONTES;

Control Neurodifuso de Humedad para un Fitotrón

Abstract

Desde que se intentó dar respuesta a cuestiones sobre el origen y la evolución de las especies en la tierra con experimentos confiables, las condiciones adversas de la naturaleza fueron el principal reto. Hoy día, un espacio donde se tenga la capacidad de manipular las condiciones ambientales, ejerciendo un control de éstas, ha sido la necesidad primordial de los diversos campos de estudio de la biotecnología. En los últimos años se han desarrollado dispositivos que son utilizados en laboratorios y centros de investigación con el _n de simular distintas posibilidades climáticas; sin embargo, el costo de _estos es demasiado elevado además que los gastos de instalación, capacitación y mantenimiento es exagerado por parte de los proveedores, generando una dependencia tecnológica en cuanto al software de control y en muchos casos el sistema de control se limita a un simple controlador ON/OFF, incumpliendo las demandas de precisión, estabilidad y tiempo de respuesta que el sector necesita. Con base en lo anterior, en este trabajo se propone un sistema de control en tiempo real basado en tecnología FPGA para el control de humedad en un fitotrón mediante un controlador neurodifuso. El sistema fue descrito en VHDL y fue implementado en un sistema embebido diseñado por el grupo HSPdigital basado en un dispositivo de alto desempeño FPGA, el cual implica flexibilidad en el sistema de control, sin restricciones de compatibilidad o dependencia de alguna tecnología en particular y que permite la integración de distintos módulos de control para dar una solución tipo SoC al control de variables ambientales; haciendo, por lo tanto, un sistema de control más eficiente, completo y genérico. Además, el controlador desarrollado está basado en técnicas de control sumamente sofisticadas como lo son la lógica difusa y las redes neuronales artificiales el cual ofrece resultados eficientes y precisos. Los resultados de las pruebas demuestran un mejor desempeño de las técnicas de inteligencia artificial en comparativa con los métodos clásicos en el control de humedad del fitotrón.

Since attempts to answer questions about the origin and evolution of species on earth with reliable experiments, the adverse conditions of nature were the main challenge. Nowadays, a place with the capacity of manipulate the environmental conditions, exercising control over these, has been the primary need of the many fields of study in biotechnology. In recent years, have been developed devices that are used in laboratories and research centers in order to simulate different weather possibilities, but their cost is too high in addition to the cost of installation, training and maintenance is exaggerated by providers, creating a technological dependence on the software control and in many cases the control system is limited to a simple ON / OFF control, in violation of the demands for precision, stability and response time that the sector needs. Based on the above, this paper proposes a control system in real time based on FPGA technology to control moisture in a phytotron through a neurofuzzy controller. The system was described in VHDL and was implemented in an embedded system FPGA-based high-performance device, which involves flexibility in the control system, unrestricted compatibility or reliance in any particular technology and allows the integration of different control modules giving a SoC solution to control environmental variables, therefore, making an efficient control system, full and generic. In addition, the developed controller is based on highly sophisticated control techniques such as fuzzy logic and artificial neural networks, which others efficient and accurate results. The results of the tests show a better performance of artificial intelligence techniques in comparison with conventional methods to control moisture in a phytotron.

Keywords

info:eu-repo/classification/cti/7, info:eu-repo/classification/cti/11

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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