Research on Neural Network Based Inverse Model of Induction Motor Drives

Since the realization of inverse model is very important for inverse decoupling control of induction motor (IM) drives, the purpose of this paper is to develop an efficient artificial neural network (ANN) based inverse model for IM drives. First, the existence of the inverse system for IM drives is proved by inverse system theory. However, the analytic inverse model is hardly applied in the engineering since it excessively depends on the parameters. Then a novel neural network based inverse model, which synthesizes non-analytic method and analytic method, is suggested in this paper. To accelerate the convergence speed of ANN and enhance its generalization ability, the nonlinear parts are realized by the analytic expressions and the corresponding results act as the inputs of network. A three-layered feed-forward ANN with 11-40-2 structure is introduced to approach the inverse mode of IM drives. This study shows that the procedure using ANN based inverse model is applicable to substitute the analytic inverse model of IM drives. Simulation results are given to verify the developed models.