Volume -I , Issue -III, February 2014

IMPLEMENTATION OF GENETIC ALGORITHM TO TEMPERATURE CONTROL SYSTEM

Author(s) :

Pooja Khatri and Manjeet Dalal

Abstract

During the last years the use of intelligent strategies for tuning of controller has been growing. The evolutionary strategies have won an important place, thanks to their flexibility. The first attempt to automate the tuning of controllers was based on the time response of a process, but this approach had the drawback of requiring a lot of user interaction. A very important advancement was made when it was decided to use the frequency response of a process instead of its time response, in this way a bigger degree of automation was obtained. Optimal tuning plays on important role in operations or tuning in the complex process such as the temperature of an oven used in many industrial applications. Transfer of heat inside an oven requires a delay or transportation lag. So, this delay or transportation lag is overcome with the help of controller tuning using Genetic Algorithm. A comparison approach is also made with the other methods of tuning like Ziegler-Nicholas. Genetic algorithm is powerful software tool for obtaining accurate results. It works same as the combination of genes in biological processes. Any temperature control system like oven take certain time to heat up initially , But with the help of genetic algorithm this time taken to heat up can be reduced. And the oven can be made to start instantly without wasting time. It is very difficult to achieve an optimal gain like this as up to the present time the gain of the controller has to be manually tuned by hit and trial. Thus this paper describes the Genetic algorithm approach that would certainly reduce manual effort and give accurate result

Keywords

Genetic Algorithm, intelligent strategies, evolutionary strategiesn

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How to Cite this Paper? [APA Style]
Pooja Khatri and Manjeet Dalal, (2014), IMPLEMENTATION OF GENETIC ALGORITHM TO TEMPERATURE CONTROL SYSTEM, Industrial Science Journal, http://industrialscience.org/Article.aspx?aid=20&vid=3, (February, 2014)
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