期刊文献+

感应电机高阶终端滑模磁链观测器的研究 被引量:38

High-order Terminal Sliding Mode Flux Observer for Induction Motors
下载PDF
导出
摘要 提出了基于高阶非奇异终端滑模的感应电机转子磁链观测方法,用于实现感应电机的按转子磁链定向控制.设计了非奇异终端滑模面及观测器的控制策略,利用所设计的控制策略推导出电机转子磁链信息.为了抑制常规滑模存在的抖振现象,设计了定子电流观测器的高阶滑模控制律,可将控制信号直接用于电机转子磁链的估计.较常规滑模观测器,所提方法具有较高的观测精度,并对电机参数变化具有良好的鲁棒性.仿真结果验证了方法的有效性. This paper proposes a rotor flux estimation method based on high-order sliding mode and non-singular terminal sliding mode for implementing the field orientation control of induction motors. A nonsingular terminal sliding mode and the control law of the observer are designed. The rotor flux of the motor is deduced using the designed control law. Meanwhile, the high-order sliding mode technique is adopted to eliminate the chattering phenomenon of the conventional sliding mode so that the control signal of the observer can be used directly for rotor flux estimation. Compared to conventional sliding mode observers, the proposed observer can estimate the system state with a higher precision. Further, it is insensitive to parameter variations. Simulation results validate the proposed method.
作者 史宏宇 冯勇
出处 《自动化学报》 EI CSCD 北大核心 2012年第2期288-294,共7页 Acta Automatica Sinica
基金 国家自然科学基金(61074015)资助~~
关键词 磁链观测器 非奇异终端滑模 高阶滑模 感应电机 Flux observer non-singular terminal sliding mode high-order sliding mode induction motor
  • 相关文献

参考文献5

二级参考文献59

  • 1祝龙记,王宾.基于MRAS速度辨识矢量控制系统的仿真研究[J].电工技术学报,2005,20(1):60-65. 被引量:35
  • 2高为炳.离散时间系统的变结构控制[J].自动化学报,1995,21(2):154-161. 被引量:134
  • 3刘毅,贺益康,秦峰,贾洪平.基于转子凸极跟踪的无位置传感器永磁同步电机矢量控制研究[J].中国电机工程学报,2005,25(17):121-126. 被引量:99
  • 4万军,王建海,万敏,马彦兵.使用基频电流注入的感应电机无速传感器驱动[J].中国电机工程学报,2005,25(22):163-167. 被引量:13
  • 5Ren X M, Chen J. A modified neural network for dynamical system identification and control. In: Proceedings of the 14th World Congress of International Federation of Automatic Control. Beijing, China: IFAC, 1999. 463-468.
  • 6Spooner J T, Maggiore M, Ordonez R, Passino K M. Stable Adaptive Control and Estimation for Nonlinear Systems. New York: Wiley and Sons, 2002. 49-69.
  • 7Hayakawa T, Haddad W M, Hovakimyan N. Neural network adaptive control for a class of nonlinear uncertain dynamical systems with asymptotic stability guarantees. IEEE Transactions on Neural Networks, 2008, 19(1): 80-89.
  • 8Chen J, Peng Z H, Cao L J, Gao T T. RBF neural network based human genome TSS identification. In: Proceedings of the 16th IFAC World Congress. Prague, Czech: IFAC, 2005. 13-14.
  • 9Cotter N E. The Stone-Weierstrass theorem and its application to neural networks. IEEE Transactions on NeurM Networks, 1990, 1(4): 290-295.
  • 10Wang D, Huang J. Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form. IEEE Transactions on Neural Networks, 2005, 16(1): 195-202.

共引文献77

同被引文献360

引证文献38

二级引证文献295

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部