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Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms

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Abstract

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers, under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with the evolutionary algorithm outperform type-1 fuzzy controllers.

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Authors and Affiliations

  1. Tijuana, Institute of Technology, Tijuana, BC, Mexico

    O. Castillo, P. Melin & A. Alanis

  2. Center for Research in Digital Systems, IPN, Tijuana, BC, Mexico

    O. Montiel & R. Sepulveda

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  1. O. Castillo
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  2. P. Melin
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  3. A. Alanis
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  4. O. Montiel
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  5. R. Sepulveda
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Correspondence to O. Castillo.

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Castillo, O., Melin, P., Alanis, A. et al. Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms. Soft Comput 15, 1145–1160 (2011). https://doi.org/10.1007/s00500-010-0588-9

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