CONTROL DIFUSO PD+I TAKAGI-SUGENO-KANG PARA UN SISTEMA DE AIRE ACONDICIONADO

Juan Carlos Zaragoza Hernandez, Jaime Jalomo Cuevas, Armando García Mendoza

Resumen


Resumen

Los sistemas de aire acondicionado generalmente son operados mediante un controlador simple ON/OFF, ya que estos son simples y fáciles de implementar o con el control tradicional PID. Sin embargo, el rendimiento de estos sistemas no suele ser preciso, tienen un alto consumo de energía y un gran desgaste en el funcionamiento del compresor. Este artículo presenta la implementación del método difuso Takagi-Sugeno-Kang (TSK) para el control de temperatura en el aire acondicionado, con el objetivo de aumentar la eficiencia del sistema, mejorar el rendimiento y reducir el consumo de energía. Los resultados obtenidos en simulación y pruebas físicas demuestran que el uso del control difuso PD+I con el método TSK es eficiente para ahorrar energía, es estable al cambio en la carga térmica y con una rapidez de respuesta en la regulación de temperatura con errores no superiores al 2%.

Palabras Clave: Aire acondicionado, Control difuso PD+I, Método difuso.

 

FUZZY CONTROL PD+I TAKAGI-SUGENO-KANG FOR AN AIR CONDITIONING SYSTEM


Abstract

The air conditioning systems are generally operated by a simple ON/OFF controller since this is easy to implement or with the traditional PID control. However, the performance of these systems is not usually precise, they have a high energy consumption and a great mechanical wear on the compressor operation. This article presents the implementation of the Takagi-Sugeno-Kang fuzzy method (TSK) for temperature control in air conditioning, with the aim of increasing system efficiency, improving performance and reducing energy consumption. The results obtained in simulation and physical tests show that the use of PD + I fuzzy control with the TSK method is effective to save energy, stable to the change in thermal load and has a rapid response in temperature regulation with errors not exceeding 2%.

Keywords: Air conditioning, Fuzzy control PD+I, Fuzzy method.


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Referencias


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