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 facing with unpredictable

disturbance and uncertainties. Therefore Type-2 fuzzy sets was 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 footprint of uncertainty. This paper

presents a Bacterial Foraging Optimization approach for optimizing the parametrized

membership function. The above criterion is applied to an Automatic Voltage Regulator

system and results are presented and compared with previous method. -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　facing　with　unpredictable

disturbance　and　uncertainties.　Therefore　Type-2　fuzzy　sets　was　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　footprint　of　uncertainty.　This　paper

presents　a　Bacterial　Foraging　Optimization　approach　for　optimizing　the　parametrized

membership　function.　The　above　criterion　is　applied　to　an　Automatic　Voltage　Regulator

system and results are presented and compared with previous method.