Speed sensorless control for induction motor based on flux observer with Petri fuzzy neural networks
基于Petri模糊神经网络磁通观测器的感应电动机无速度传感器控制

Pertri fuzzy neural networks(PFNN) are applied to construct the current observer. The flux observer is constructed based on the observed current. The rotor speed is computed according to the observed rotor flux. Slidingmode backstepping controllers are designed based on a new decoupled model of the induction motor. The proof of PFNN convergence is also given. The effectiveness of the control design is validated through MATLAB simulation.