Intelligent sensorless control of two-phase linear brushless DC motor based on a recurrent fuzzy neural network

This paper presents a recurrent fuzzy neural network (RFNN) controller to provide sensorless speed control for the two-phase linear brushless DC motor. It is not easy to arrange current and speed sensors along the linear motor's required railway. The RFNN controller has the capability of tracing the system dynamics due to the inherent learning function. With the help of RFNN controller, the conventional PID control can be made to provide better performance by tracing the system dynamics. The paper will demonstrate dynamic performance improvement scenarios. The recurrent structure also enhances the conventional fuzzy neural network (FNN) controller with embedded memory function. The results from experimental evaluation indicate that the PID with RFNN controller can provide better performance than the conventional PID controller.