A bacterial foraging optimization approach for tuning type-2 fuzzy logic controller

The type-1 fuzzy sets theory was proposed to handle uncertainty in control systems, but some cases showed some liabilities of type-1 fuzzy sets when faced with unpredictable disturbance and uncertainties. Therefore, type-2 fuzzy sets were introduced and extended while providing more degrees of freedom in designing criteria. The most important specification of type-2 fuzzy sets is the interval between a superior membership function and an inferior membership function, which is called the footprint of uncertainty. This paper presents a bacterial foraging optimization approach for optimizing the parameterized membership function. The above criterion is applied to an automatic voltage regulator system and results are presented and compared with the previous method.

A bacterial foraging optimization approach for tuning type-2 fuzzy logic controller

The type-1 fuzzy sets theory was proposed to handle uncertainty in control systems, but some cases showed some liabilities of type-1 fuzzy sets when faced with unpredictable disturbance and uncertainties. Therefore, type-2 fuzzy sets were introduced and extended while providing more degrees of freedom in designing criteria. The most important specification of type-2 fuzzy sets is the interval between a superior membership function and an inferior membership function, which is called the footprint of uncertainty. This paper presents a bacterial foraging optimization approach for optimizing the parameterized membership function. The above criterion is applied to an automatic voltage regulator system and results are presented and compared with the previous method.

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