Research On Parameter Identification And Control Strategy Of Induction Motor

Induction motor that has been widely used in modern industry has some advantages such as high reliability,excellent performance and so on.The occurrence of vector control makes it possible to acquire high-performance control of induction motor,but the change of motor parameters have an important influence on the vector control of induction motor.In order to improve the performance of vector control of induction motor,parameters identification and vector control with parameters identification of induction motor are studied in this paper.1.In order to solve the problem of low accuracy of parameters identification based on intelligent algorithms in the classical parameter identification model of induction motor,an improved model which combines two classical models is proposed.The improved identification model firstly uses the model whose state variables are rotor flux linkage and stator current and then uses another model whose state variables are stator flux linkage and stator current.The improved model is proved to be correct by experiment compared with the classical model.Grey wolf optimizer has some advantages such as simpleness and practicality,less adjustment parameters and better searching ability.On account that parameters estimation are not accurate in the vector control of induction motor,grey wolf optimizer is applied to identify motor parameters.Compared with particle swarm optimization and genetic algorithm,the simulation results show that grey wolf optimizer has more accurate identification ability.2.Aiming at improving the accuracy of inductances identification based on the improved model,a transformation model I is proposed.The transformation model I based on the improved model uses circularly two classical models in the two-phase stationary coordinate.Compared with the improved model mentioned above,it is proved that the transformation model I can improve the accuracy of inductances identification.In order to further improve the identification accuracy of motor parameters,a transformation model II based on transformation model I is proposed.Transformation model II is that two classical models in the two-phase stationary coordinate are applied circularly.Meanwhile,the best value based on one model is used to initialize one value of the other model.In contrast to the three proposed models,the simulation results show that identification effect of motor parameters are improved when transformation model II is applied as the identification model.3.With the aim of improving the performance of the vector controlled induction motor,a novel control method which combines variable structure PID speed control with online identification of rotor resistance based on model reference adaptive system(MRAS)is proposed.In this paper,the identification of rotor resistance based on MRAS is fed back to the vector control of induction motor.Given that the parameters of traditional PID speed regulator can not change on line and the integral saturation phenomenon often exists,a variable structure PID speed controller is designed by integrating traditional PID,anti-windup technology with fuzzy theory.It can be seen from the MATLAB simulation experiment that the proposed controller can relieve the integral windup phenomenon of the system and reduce speed overshoot.Meanwhile,rotor resistance identification based MRAS is proved to effective in variable structure PID speed control.