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兵工学报 ›› 2013, Vol. 34 ›› Issue (6): 739-747.doi: 10.3969/j.issn.1000-1093.2013.06.013

• 研究论文 • 上一篇    下一篇

无刷直流电机反电势滑模观测及参数在线辨识

史婷娜, 张茜, 肖有文, 夏长亮   

  1. 天津大学电气与自动化工程学院, 天津300072
  • 上线日期:2013-08-27
  • 作者简介:史婷娜(1969—),女,副教授,硕士生导师
  • 基金资助:

    国家自然科学基金项目(51037004)

Online Parameter Identification and Sliding Mode Observation of Back-electromotive Force of Brushless Direct Current Motors

  1. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China
  • Online:2013-08-27

摘要:

传统滑模状态观测器(SMO)性能依赖于准确的电机数学模型,电机定子电阻及电感参数偏差会对观测结果造成一定影响。针对这一问题,分析了电阻与电感偏差值对观测结果的影响形式;基于Lyapunov 稳定性理论,设计了新型自适应SMO,实现了无刷直流电机( BLDCM) 线反电势观测及定子电阻和电感参数的同时在线辨识。最后,通过仿真与实验验证了理论的正确性,证明了所提方法能够在一定程度上消除参数偏差对观测器的影响,较为迅速准确地辨识出定子电阻与电感值。

关键词: 电气工程, 无刷直流电机, 反电势观测, 滑模状态观测器, 参数辨识, Lyapunov 稳定性理论

Abstract:

The performance of the traditional sliding mode observer (SMO) depends on the accurate mathematical model of the motor; consequently the deviation values of stator resistance and inductance generated during operation impact the observation. The effects of their deviation values on the observed result are analyzed. Then, Lyapunov stability theory is employed to design a novel adaptive SMO by which the observation of linear back-electromotive force of a brushless direct current motor (BLDCM) is achieved and the online identification of the stator resistance and inductance is implemented simultaneously. Simulation and experiment results demonstrate that the proposed strategy can be used to mitigate the impact of parameter error on the observer performance to some extent and estimate the stator resistance and inductance.

Key words: electrical engineering, brushless direct current motor, back-electromotive force observation, sliding mode observer, parameter identification, Lyapunov stability theory

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