FGA temperature control for incubating egg

  • Authors:

  • Ismail Yusuf;Yusram Yusuf;Nur Iksan

  • Affiliations:

  • Department of Computer, Lamintang Education and Training Indonesia, Kepri, Indonesia and Department of Information Technology, Sekolah Tinggi Teknik, IBNU, SINA, BATAM, Kepri, Indonesia;Department of Mechanical Enginering, Sekolah Menengah Kejuruan, Sulawesi Selatan, Indonesia;Department of Computer, Lamintang Education and Training Indonesia, Kepri, Indonesia

  • Venue:
  • Advances in Fuzzy Systems - Special issue on Fuzzy Functions, Relations, and Fuzzy Transforms: Theoretical Aspects and Applications to Fuzzy Systems
  • Year:
  • 2012

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Abstract

This paper investigates the use of genetic algorithms (GA) in the design and implementation of fuzzy logic controllers (FLC) for incubating egg. What is the best to determine the membership function is the first question that has been tackled. Thus it is important to select the accurate membership functions, but these methods possess one common weakness where conventional FLC use membership function generated by human operators. The membership function selection process is done with trial and error, and it runs step by step which takes too long in solving the problem. This paper develops a system that may help users to determine the membership function of FLC using the GA optimization for the fastest processing in solving the problems. The data collection is based on the simulation results, and the results refer to the transient response specification which is maximum overshoot. From the results presented, we will get a better and exact result; the value of overshot is decreasing from 1.2800 for FLC without GA to 1.0081 with GA (FGA).