基于CESO磁链观测器的模型参考自适应感应电机转速辨识

针对感应电机无速度传感器矢量控制下的速度辨识问题,设计了一种基于扩展状态观测器的闭环转子磁链观测器(CESO),并提出以其作为参考模型的模型参考自适应(CESO-MRAS)转速辨识方法。该磁链观测器将模型中不确定部分进行状态扩展并反馈补偿,是一种闭环观测器,因而对电机转子电阻变化以及外部扰动具有良好的鲁棒性,克服了传统电压转子磁链模型的纯积分和低速区的电压降问题。通过与传统MRAS的仿真比较研究,在转子电阻和转矩的大范围变化低速区,该算法能显著提高矢量控制系统的速度动态辨识能力和转矩抗扰能力。仿真和实验结果验证了该方法的正确性和有效性。

Speed identification for induction motor based on CESO flux observer and MRAS

Flux observer based on closed loop extended-state-observer ( CESO) and model reference a-daptive system ( MRAS) based estimation algorithms were proposed in the thesis,and used in the speed-sensorless vector controlled induction motors ( IMs) system.A modified flux estimation model using CESO and integrated with flux compensate technology is introduced to reduce the uncertainty of the IMs model. Sensitivity of the sensorless drive against parameter and measurement errors is also qualitatively dis-cussed.The speed identification algorithms is less sensitive to integration-related problems such as satura-tion and voltage drop at low speed,and its accuracy is independent the rotor resistance and torque varia-tions as well.Simulations and experimental results proved the validity and practicability of the algorithm by comparing with classic MRAS method.