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This paper proposes a novel approach of nonlinear model predictive control using multi-model structure. Firstly, a nonlinear discrete time system is locally linearized and represented by a multi-model structure. A local state feedback control is used so that the family of the linear models has the similar dynamics. Then a model predictive control strategy based on Laguerre functions is designed to make each linear system optimal for a given cost function. Finally, a novel switching strategy is proposed to make the multi-model system satisfy the given performances. The simulation results are presented to validate the method.