Study On Speed Sensorless Vector Control System Of Induction Machine Based On Improved MRAS Model

In recent years, vector control is increasingly getting the favor of people. It has good performance and robustness, was commonly used in induction motor variable frequency speed regulation system. Application of vector control technology not only promoted the development of AC drive technology, but also increases the market share of inverter equipment. In vector control system, speed loop is of major importance, which directly affects the accuracy of flux observer and speed control. In practice, people often adopt a speed detection device to obtain the actual speed of the motor, it not only increases the purchase cost of equipment, but also the equipment maintenance and maintenance are very inconvenient. The other hand, the long running will make measurement results produce error, which affects the control effect of the system. The application of sensorless vector control system can effectively solve the above problems, has become one of the most commonly used control methods. This paper focuses on the speed estimating models, motor parameter identification and improved MRAS model and other aspects of the study, and the use of MATLAB to verify the feasibility of the system.First of all, in order to get the actual rotation speed of the motor, this paper uses the model reference adaptive system(MRAS) to estimate the speed of the motor. At the same time, to reduce the influence of motor parameters on speed estimation model, this paper uses an off-line parameter identification of induction motor based on recursive least-squares(RLS) algorithm. In addition, using improved voltage flux model and variable-parameter PI controller to improve the performance of the sensorless vector control, the latter could real time adjustment of PI parameters according to the flux deviation. In this paper, a novel rotor speed estimation method using MRAS is proposed to improve the performance of a sensorless vector control in the very low speed region. In the new MRAS method, two differences are used at the same time. The first is between rotor fluxes and the second between electromagnetic torques. The adaptive mechanism used in this new structure contains two parallel loops having PI controller and low-pass filter. The first and the second loops are used to adjust the rotor flux and electromagnetic torque.Secondly, this paper uses MATLAB to build the simulation model of the system, theoretically verified the feasibility of the system. Simulation results show the effectiveness of the proposed speed estimation method and parameter identification. In addition, using the proposed speed estimation method could improve estimation accuracy in the low regions.Finally, to verify the above solution, this paper builds system experimental platform based on DSP controller. The experimental results show that this system can meet the requirements, speed identification in real time tracking rotor speed change.