Synchronous motor speed control based on ANFIS methodology and sliding mode observer

The application of artificial intelligence has become an important topic in electrical machines control. This paper presents an application of neuro-fuzzy NF control for synchronous motor SM speed. The NF has the advantages of expert knowledge of the fuzzy inference system and the learning capabilities of neural networks. A neuro-fuzzy controller of the motor speed is then designed and simulated. An asymptotically stable observer is designed to overcome the problem of speed sensor and is obtained without affecting the overall system response. Digital simulation results show that the designed NF speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of load disturbances.