Comparison of the Optimal Design of Fuzzy Controllers for the Water Tank Using Ant Colony Optimization

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 547)

Abstract

A study of the behavior and evaluation of the Ant Colony Optimization algorithm (ACO) in Type-1 and Type-2 Fuzzy Controller design is presented in this chapter. The main objective of the work is based on the main reasons in tuning membership functions for the optimization Fuzzy Controllers of the benchmark problem known as the Water Tank with the algorithm of Ant Colony Optimization. For the design of Type-1 and Type-2 Fuzzy Controllers for particular applications, the use of bio-inspired optimization methods have helped in the complex task of finding the appropriate values of the parameters and the structure of fuzzy systems. In this research we consider the application of ACO as the paradigm that aids in the optimal design of Type-1 and Type-2 Fuzzy Controllers. We also analyzed that in evaluating the uncertainty, the results in the simulation are better with Type-2 Fuzzy Controllers. Finally, provide a comparison of the different methods for the case of designing Type-1 and Type-2 Fuzzy Controllers with Ant Colony Optimization.

Notes

Acknowledgments

We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Tijuana Institute of TechnologyTijuanaMexico

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