Research of Neuro-Fuzzy-Based Hybrid Efficiency Optimization Control of Inductive Motor

The efficiency of inductive motor can obtain the maximum value in the rating working condition, but will decrease obviously in the light load status. A method in the efficiency optimizing of inductive motor is introduced in this paper. In the vector controlled inductive motor system, a hybrid energy saving control method is put forward. In this method, neural network, fuzzy logic and Rosenbrock searching algorithm are combined in one system. Compared with the performance of using these algorithms separately, some problems such as torque variation, local optimization and system divergence can be solved partly in this method. The simulation results show that the system achieves high efficiency operation by using the proposed method, when the load is changed. The energy saving target is obtained.