Big Bang Big Crunch Optimization Method Based Fuzzy Model Inversion

Kumbasar T., Eksin İ., Guzelkaya M., Yesil E.

7th Mexican International Conference on Artificial Intelligence (MICAI 2008), Atizapan de Zaragoza, Mexico, 27 - 31 October 2008, vol.5317, pp.732-740 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 5317
  • Doi Number: 10.1007/978-3-540-88636-569
  • City: Atizapan de Zaragoza
  • Country: Mexico
  • Page Numbers: pp.732-740
  • Istanbul Technical University Affiliated: Yes


The inverse fuzzy model can be used as a controller in an open loop fashion to produce perfect control if there does not exist any disturbance or parameter variation in the system. In this paper, a new fuzzy model inversion technique that is based on an evolutionary search algorithm called Big Bang Big Crunch (BB-BC) optimization is introduced. Even though various fuzzy inversion methods can be found in literature, these methods are only applicable under certain conditions or limitations. On the other hand, there does not exist any limitation or condition for the new methodology presented here. In this new technique, the inverse fuzzy model control signal is generated iteratively as a consequence of an optimization operation. Since the BB-BC optimization algorithm has a high convergence speed and low computational time, the optimal inverse fuzzy model control signal is generated within each sampling time. The beneficial sides of the open loop control approach based on the proposed fuzzy model inversion technique are illustrated through two simulation studies.