【摘要】 为了提高永磁同步直线电机(PMLSM)的跟随精度，提出了一种基于闭环辨识模型的分数阶反馈控制方法，通过对反馈控制系统误差幅值特性进行特定分数阶次形式的精准调节来有效抑制PMLSM的跟随误差。该方法推导了PMLSM闭环辨识模型，通过误差幅值特性分析，确定了分数阶超前-滞后补偿器参数选定方法，以实现分数阶反馈控制系统对PMLSM控制频域特性的准确描述，进而提高PMLSM辨识精度及控制性能。采用所提方法在PMLSM龙门运动平台上进行辨识方法和不同运动规划的跟踪实验及圆轨迹运动实验的验证，实验结果表明，该闭环辨识方法能有效抑制外界对辨识信号的干扰，所建立的闭环辨识模型准确性高；相较于PID控制方法，所提分数阶反馈控制方法能够大幅减小PMLSM跟随误差，对于不同运动规划，跟随误差的均方根误差值减小至少82.47%,验证了所提方法可有效提高PMLSM跟踪精度。更多还原

【Abstract】 In order to improve the tracking accuracy of PMLSMs, a fractional-order feedback control method was proposed based on closed-loop identification model. By precisely adjusting the error amplitude characteristics of the feedback control system in a specific fractional-order form, the following errors of PMLSMs might be effectively suppressed. A closed-loop identification model was derived for the PMLSM and the parameter selection method of the fractional-order lead-lag compensator was determined based on analysis of the error amplitude characteristics. With the properly defined fractional-order parameters, the fractional-order feedback control system might accurately describe the frequency-domain characteristics of the PMLSM, and the identification accuracy and control performance of the PMLSM might thus be improved. The proposed method was experimentally validated on a PMLSM gantry motion platform through identification methods, tracking experiments with different motion planning, and circular trajectory motion experiments. The experiments on system closed-loop identification and motion tracking with different plannings were performed. The experimental results show that the closed-loop identification method may effectively suppress the influences of external interferences on the identification signals, and the closed-loop identification model is accurate for the control system, the proposed fractional-order feedback control method may greatly reduce the tracking errors of the PMLSMs, and compared to the PID control method, the proposed control method may reduce the root mean square error(RMSE) tracking errors by at least 82.47% under different motion scenarios. The experimental results demonstrate the effectiveness of the proposed method in improving the tracking accuracy of PMLSMs.更多还原