Research On SRM Controller Based On Non-Position Sensor

Switched Reluctance Motor (SRM) has simple structure, low maintenance cost, efficient variable speed performance and many control methods, these advantages has been favored by scientific researchers from all walks of life. The rotor position angle of Switched Reluctance Drive (SRD) is provided by the position sensor traditionally. But position sensor weakens the advantages in simple stucture of the motor. In addition.Position sensor is more sensitive to the environment, which (?) limits the wide application of SRM certainly. So non-position sensor has become a hot spot in the field of SRM. The key point of this paper is to detect the motor position information by using the non-sensor detection method to realize the speed control of switched reluctance motor.This paper analyzes the speed control principle of switched reluctance motor and determines a speed control system of switched reluctance motor based on fuzzy neural network to achieve position angle detection.The system adopts double closed-loop strategy,in which the inner loop is current chopping controller and the outer loop is PI speed controller. Firstly,This design uses the fuzzy neural network algorithm to train the undetermined parameters in the fuzzy controller, and then uses Simulink tool to build a complete simulation model of SRD based on the fuzzy neural network method. and later designs the software and hardware of SRD based on non-position sensor. The system simulation and system test results prove that non-position sensor control method proposed in this paper has certain recognition ability,and the motor speed based on non-position sensor can run well.