感应电机参数辨识及控制策略研究

发布时间：2018-04-04 04:19

本文选题：感应电机　切入点：参数辨识　出处：《江南大学》2017年硕士论文

【摘要】：感应电机具有可靠性高、性能优良等优点,在现代工业中得到了广泛应用。矢量控制的出现使感应电机的高性能控制成为可能,但电机参数变化会对其矢量控制产生重要影响。为了提高感应电机的矢量控制性能,本文对感应电机的参数辨识和带参数辨识的矢量控制问题进行了深入研究。1.针对经典的感应电机参数辨识模型,智能算法在辨识其参数时存在辨识精度低的问题,提出了一种融合两种经典模型的改进模型。该改进辨识模型先用以转子磁链、定子电流为状态变量的模型,然后在此基础上用以定子磁链、定子电流为状态变量的模型。通过与经典模型的对比实验,证明了该改进模型的正确性。苍狼算法具有简单实用、需调节参数少、寻优能力强等优点。考虑到在感应电机矢量控制中所需参数估计不准的问题,提出了一种基于苍狼算法的参数辨识方法。通过与粒子群算法和遗传算法的对比实验,仿真表明苍狼算法具有更准确的辨识能力。2.为了提升改进模型的电感辨识精度,提出了一种变换模型I。该变换模型I以改进模型为基础,循环使用两相静止坐标下的两种经典模型。通过与上面所提改进模型对比实验,证明了变换模型I能够提升电感的辨识精度。为了进一步提升电机参数的辨识精度,在变换模型I的基础上提出了一种变换模型II。变换模型II是指:循环使用两相静止坐标下的两种经典模型,同时将一种模型辨识的最优值作为下种模型中的一个初值。将所提出的三种模型进行对比实验,仿真表明以变换模型II为辨识模型时改善了电机参数的辨识效果。3.为了改善感应电机矢量控制性能,提出了一种变结构PID速度控制与基于模型参考自适应(MRAS)转子电阻在线辨识相结合的控制方法。本文将基于MRAS辨识的转子电阻在线反馈到电机的矢量控制系统中。考虑到传统PID控制器参数不能在线改变并存在积分饱和现象,结合传统PID速度控制器、anti-windup技术和模糊理论设计了一种变结构PID速度控制器。由MATLAB仿真实验可以看出,所提控制器缓解了系统的积分饱和现象,减小了速度超调;同时证明了在变结构PID速度控制下基于MRAS转子电阻辨识的有效性。
[Abstract]:Induction motor has been widely used in modern industry because of its high reliability and excellent performance.The emergence of vector control makes the high performance control of induction motor possible, but the variation of motor parameters will have an important impact on the vector control.In order to improve the vector control performance of induction motor, the parameter identification and vector control with parameter identification of induction motor are studied in this paper.Aiming at the problem of low identification accuracy in the classical parameter identification model of induction motor, an improved model combining two classical models is proposed.The improved identification model first uses the rotor flux and stator current as the state variable, and then uses the stator flux as the state variable and the stator current as the state variable.The correctness of the improved model is proved by comparison with the classical model.The algorithm has many advantages, such as simple and practical, less adjustment parameters and better searching ability.Considering the problem of inaccurate parameter estimation in vector control of induction motor, a parameter identification method based on grey wolf algorithm is proposed.By comparing with particle swarm optimization algorithm and genetic algorithm, the simulation results show that the algorithm has more accurate identification ability.In order to improve the accuracy of inductance identification of the improved model, a transformation model is proposed.The transformation model I is based on the improved model and uses two classical models in two phase stationary coordinates.By comparing with the improved model, it is proved that the transformation model I can improve the accuracy of inductor identification.In order to further improve the identification accuracy of motor parameters, a transformation model II is proposed on the basis of transformation model I.Transformation model II refers to the cyclic use of two classical models in two-phase stationary coordinates, and the optimal value of a model identification is taken as an initial value in the next model.The simulation results show that the identification effect of the motor parameters is improved by using the transformation model II as the identification model.In order to improve the vector control performance of induction motor, a control method combining variable structure PID speed control with on-line identification of rotor resistance based on model reference adaptive control is proposed.In this paper, the rotor resistance based on MRAS identification is fed back to the vector control system of the motor.Considering that the parameters of the traditional PID controller can not be changed on line and the integral saturation phenomenon exists, a variable structure PID speed controller is designed by combining the anti-windup technique and fuzzy theory of the traditional PID speed controller.The simulation results of MATLAB show that the proposed controller can reduce the integral saturation and speed overshoot of the system and prove the effectiveness of the rotor resistance identification based on MRAS under the variable structure PID speed control.
【学位授予单位】：江南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM346

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