Research On Speed Sensorless Vector Control System Of Induction Motor

The Induction motor high-performance speed control system needs to install photoelectric encoder.When the concentricity accuracy is less than 50 um,closed loop control cannot be achieved.At the same time,the encoder signal is susceptible to electromagnetic interference,and the installation of an encoder increases the complexity of the induction motor frequency conversion speed regulation hardware system.Therefore,the speed sensorless technology using the relevant algorithm to estimate the speed by collecting the motor stator voltage,current and other signals has become a research hotspot.At present,there are mainly two control schemes based on the basic model of the motor and based on the anisotropy of the motor.This paper focuses on the problems of low-speed oscillation and sensitivity to measurement noise in the speed sensorless vector control system,based on the observer method of the basic motor model,the speed sensorless vector control system of induction motor is studied.Firstly,the dynamic mathematical model of the induction motor has the properties of high-order,nonlinear and strong coupling.And through the vector coordinate transformation,the dynamic mathematical model of the induction motor is simplified.Secondly,for the induction motor at low and medium speeds,there are speed oscillations,weak immunity,and low speed estimation accuracy,a speed estimation method combining the Model Reference Adaptive System(MRAS)observer and the sliding mode observer based on the rotor flux model and using genetic algorithms to optimize the parameters of the sliding mode observer is proposed,and a control strategy combining flux linkage,speed fuzzy PI controller and current sliding mode controller is designed.The simulation results show that the proposed method can effectively reduce the amplitude of low-speed speed oscillation in the induction motor,and improve the anti-disturbance performance and speed estimation accuracy.Furthermore,aiming at the problem that when the induction motor runs at high speed,the nonlinear changes of the motor parameters cause the system noise and measurement noise to increase the influence of the signal,research on speed sensorless technologybased on Extended Kalman Filter(EKF).In order to enhance the robustness of the induction motor speed sensor system to motor parameters and external environmental changes and measurement noise interference,a speed estimation method based on Strong Tracking Extended Kalman Filter(STEKF)is designed.And adopt voltage decoupling controller to eliminate the coupling voltage of dq axis.In order to solve the problem that the noise matrix parameters are not easy to determine,the noise matrix parameters are optimized by the global auxiliary particle swarm optimization algorithm.Simulation results show that the speed estimation method based on STEKF improves the system's anti-disturbance performance and speed estimation accuracy.Finally,by designing a switching control strategy,the improved MRAS speed estimation method and the improved EKF speed estimation method are combined to achieve an accurate estimation of the motor speed in a wide range.