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Sensorless Control for Joint Drive Unit of Lower Extremity Exoskeleton with Cascade Feedback Observer

机译:下肢外骨骼关节驱动器的无传感器控制,带级联反馈观测器

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摘要

In this paper, a sensorless control method for joint drive unit driven by BLDC motor of low extremity exoskeleton, cascade feedback observer identification method, is proposed. The cascade feedback observer identification method is based on improved Integral-Switching-Function Sliding-Mode-Observer (ISF-SMO) and adaptive FIR filter. 'the improved Integral-Switching-Function Sliding-Mode-Observer is used to identify the back-EMF of motor. The sliding mode surface redesigned according to Integral-Switching-Function (ISF) eliminates the inevitable chattering problem in conventional Sliding-Mode-Observer (SMO). The stability condition of Integral-Switching-Function Sliding-Mode-Observer is obtained with Lyapunov function. Meanwhile, considering the estimation error and system instability caused by the mismatch between the actual resistance value (R-s) and the set resistance value, the LMS algorithm is used to estimate the resistance value online according to the structure of adaptive FIR filter. When system is running, the modified Integral-Switching-Function Sliding-Mode-Observer and adaptive FIR filter are used to modify the back-EMF and the resistance value by cascading feedback relation, and the modified back-EMF value is taken as the final output of the system. Because of considering the uncertainty of resistance caused by temperature variation, the robustness and stability of the cascade feedback observer can be improved. Meanwhile, higher estimation accuracy is obtained, and operation range of sensorless control is extended, which is suitable for motor in low speed region. Finally, the correctness and validity of the proposed method are verified by simulations and experiments.
机译:提出了一种下肢外骨骼BLDC电动机驱动的联合驱动单元的无传感器控制方法,即级联反馈观测器辨识方法。级联反馈观测器识别方法基于改进的积分开关功能滑模观测器(ISF-SMO)和自适应FIR滤波器。改进的集成开关功能滑模观测器用于识别电机的反电动势。根据积分交换功能(ISF)重新设计的滑模表面消除了传统的滑模观察器(SMO)中不可避免的抖动问题。利用李雅普诺夫函数获得了积分交换功能滑模观测器的稳定性条件。同时,考虑到实际电阻值(R-s)与设定电阻值不匹配引起的估计误差和系统不稳定性,根据自适应FIR滤波器的结构,采用LMS算法在线估计电阻值。系统运行时,采用修正后的积分开关功能滑模观测器和自适应FIR滤波器,通过级联反馈关系来修正反电动势和电阻值,并以修正的反电动势值为最终系统的输出。由于考虑了温度变化引起的电阻不确定性,因此可以提高级联反馈观测器的鲁棒性和稳定性。同时,获得了较高的估计精度,并扩大了无传感器控制的操作范围,适用于低速区域的电动机。最后,通过仿真和实验验证了该方法的正确性和有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第14期|3029514.1-3029514.11|共11页
  • 作者单位

    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China;

    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China;

    Beijing Inst Precise Mechatron Controls, Beijing 100076, Peoples R China;

    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China;

    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China;

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