Adaptative Neuro-Fuzzy Inference System for Estimation of Rotor Flux of a Bearingless Induction Motor applied to Speed Control

This study presents the problem of rotor flux orientation control of bearingless induction motor. The key of this solution is the estimation of rotor flux. This work applied an inference system using fuzzy logic and the neural networks with the MATLAB®. The Adaptive Neuro-Fuzzy Inference System (ANFIS) which is based in an input-output model is used to tune the membership functions in fuzzy system. ANFIS along with the back propagation learning algorithm was applied to estimate the rotor flux and the magnetization current for the purpose of identifying bearingless induction motor angular speed. ANFIS aims at compensating possible parametric variations of the machine caused by agents such as temperature or nucleus saturation. The simulated results showed good performance. The inference proposed system will be implemented in DSP’s.