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A type-2 fuzzy logic system (FLS) is one that has at least one type-2 membership function (MF) in its rule base. Consequently, the output of the inference engine is a type-2 fuzzy set and must be type-reduced before the defuzzifier is able to convert the output set into a crisp value, type-2 FLS may not be suitable for certain real-time applications because type-reduction is very computationally intensive, especially when there are many MFs and the rule base is large. In this paper a simplified architecture for type-2 FLSs is proposed, where only one fuzzy set for each input domain is type-2 and all others are type-1. This architecture relieves the computational burden of the type-2 fuzzy system, while preserving its advantages over traditional type-1 FLSs. Two FLSs that have the proposed architecture are used to control a nonlinear SISO plant. Experimental results show that they cope well with the complexity of the plant, and can handle the modelling uncertainties better than their type-1 counterpart.