摘要
针对电机运行过程中参数变化特点,基于多新息辨识理论与随机梯度辨识算法理论,结合变遗忘因子,提出了基于变遗忘因子多新息随机梯度算法的双馈电机参数辨识方法。该方法考虑到双馈电机非线性强耦合,采用定子磁链定向的矢量控制技术,搭建双馈电机矢量控制系统采集数据,并推导dq坐标系下电机参数辨识模型的标准形式,根据算法辨识出电机电感及电阻参数。仿真结果验证了该算法的有效性。
Aiming at the characteristics of parameter variation during motor operation and the inaccuracy of the traditional parameter identification algorithm, based on the multi-innovation identification theory and the stochastic gradient identification algorithm, combined with the time-varying forgetting factor, a parameter identification method based on time-varying forgetting factor multi-innovation stochastic gradient identification algorithm is proposed to estimate the parameters of doubly fed induction machine. Considering the nonlinear and strong coupling of the doubly fed induction machine, the control system of the doubly fed induction motor is constructed by vector control technology. The standard form of the motor parameter identification model in the dq coordination system is deduced, and the motor inductance and resistance parameters are identified. The simulation results show that the time-varying forgetting factor multi-innovation stochastic gradient algorithm can accurately identify the motor inductance and resistance parameters of the doubly fed induction machine.
作者
黄旭
吴定会
郑洋
HUANG Xu;WU Ding-hui;ZHENG Yang(Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Wuxi 214122, China)
出处
《测控技术》
2019年第3期116-120,125,共6页
Measurement & Control Technology
基金
国家自然科学基金项目(61572237)
关键词
双馈电机
矢量控制
变遗忘因子
多新息随机梯度算法
doubly fed induction machine
vector control
time-varying forgetting factor
multi-innovation stochastic gradient identification algorithm
