The EKF Rotor Position Estimates And Variable Structure Control Of Brushless DC Motor

In recent years，with the development of various technologies (micro-electronicstechnology，computer technology and power electronics technology，etc.)，permanentmagnet materials and control theory，brushless DC motor has many advantages thatpeople are satisfied with such as high efficiency，small size，low weight，high powerdensity，low noise，easy to maintain，etc. Brushless DC motor owing to the advantageshas been widely used in every field of society.The conventional brushless DC motorobtains accurate rotor position signals through the rotor position sensors forcommutation and speed regulation. The existence of the position sensors brings manyunfavorable factors to the motor，such as increased costs，increased volume and lowerstability，etc. So the application of the motor is restricted in many occasions，especiallyin the occasions of high precision and stability.Therefore，position sensorless control ofthe brushless DC motor can not only overcome the drawbacks that the position sensorsbrings，but also makes the motor more widely used，and is of great practical significance.Meanwhile，the control performance of the motor itself is susceptible to the influence ofthe motor’s internal parameters and external disturbances. The control accuracy is alsoaffected by the good and bad effects of the controller.In this paper，a position sensorless control method based on Extended KalmanFilter(EKF）for the brushless DC motor is presented.The Extended Kalman Filter isemployed to estimate the rotor position and speed.Thus the method solves the problemscaused by the position sensor. On the other hand，the performance of the brushless DCmotor drives degrades with parameter and load variations.To slove this problem，asliding mode variable structure controller of the brushless DC motor based onexponential reaching law is also designed in this paper.Firstly， the paper simply elaborates the structure， principle and operatingcharacteristics of the brushless DC motor and introduces the position sensorless controltheory by EMF. Then the paper compares the several commonly used indirect detectionsof the rotor position.Further， the Extended Kalman Filter method as a positionsensorless control method estimates the motor speed and position. The principle of theExtended Kalman Filter (EKF) algorithm is highlighted. On this basis the ExtendedKalman Filter (EKF) algorithm will be applied to the motor control system.This methodcan not only eliminate the adverse influences of model error，measurement error， outside interference and load changes，but also estimate rotor speed and position byavailable measured stator phase current，phase voltage.At the same time，the simulationmodel of the position sensorless control system based on the EKF in Matlab/Simulinkenvironment is constructed. The simulation results demonstrate the feasibility ofEKF-based position sensorless control to estimate rotor position and velocity.Finally，this paper describes the basic principle，design method and applicationproblems of the sliding mode variable-structure. According to the characteristic thatsliding mode control in nonlinear systems is against external disturbances and parameterperturbation，a strategy of sliding mode control with exponential reaching law wasdesigned to apply in speed system based mathematical model of the brushless DC motor.Quasi-sliding mode can further improve the buffeting affect. At the same time，simulation experiments were executed in Matlab/Simulink software， results ofsimulation experiments show the control strategy compared PI control strategy made thesystem has well robustness for external disturbance and parameter perturbation，fastdynamic response and well tracking performance.