An expanded T-S model is proposed based on the conventional T-S model. This model is comprised of a set
of fuzzy rules. According to the premise part of the rules, the input space can be partitioned, and the membership values
and their transformations are introduced in the consequent part of the rules to express the nonlinear mapping relation in the
input subspace. To construct the model, the improved quantum genetic algorithm is used to optimize the premise part of the
rules, and the recursive least squares method is used to determine the parameters in the consequent part of the rules. Through
the identification of two nonlinear systems, simulation results show that the proposed model can improve the approximation
accuracy and have excellent generalization ability.