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基于级联惯性负载转矩观测器的永磁伺服电机复合抗扰控制

PMSM Composite Disturbance Rejection Control Based on Cascaded Inertia Load Torque Observers
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摘要 针对永磁伺服电机在运行时位置跟踪精度差和抗干扰性能弱等问题,提出一种模型预测位置控制与非奇异快速终端滑模速度控制相结合的复合模型预测控制策略。该控制策略采用非奇异快速终端滑模设计速度控制器,以有效提高响应速度及系统鲁棒性;采用模型预测位置控制提高位置跟踪精度;同时,采用基于转动惯量观测和负载转矩观测器相结合的级联惯性负载转矩观测器观测负载转矩并进行前馈补偿,进一步提高系统的抗干扰性能。通过仿真和实验结果可得,所提复合模型预测控制可有效提高永磁伺服电机的动态响应速度和抗负载扰动能力。 In view of the flaws of poor position tracking accuracy and weak anti-interference performance of permanent magnet servo motors during operation,a composite model predictive control strategy has thus been proposed,with model predictive position control combined with non-singular fast terminal sliding mode speed control.The control strategy adopts a non-singular fast terminal sliding mode design speed controller for an effective improvement of the response speed and system robustness,with the model predictive position control adopted for an improvement of the position tracking accuracy.Meanwhile,a cascaded inertial load torque observer,which is based on the combination of rotational inertia observation and load torque observers,is adopted to observe the load torque and perform feed-forward compensation,thus further improving the anti-interference performance of the system.Based on simulation and experimental results,it can be concluded that the proposed composite model predictive control helps to effectively improve the dynamic response speed and load disturbance resistance of permanent magnet servo motors.
作者 彭诚 王兵 易志萱 李赐图 PENG Cheng;WANG Bing;YI Zhixuan;LI Citu(College of Electrical and Information Engineering,Hunan University of Technology,Zhuzhou Hunan 412007,China;Hunan Provincial Key Laboratory of Electric Drive Control and Intelligent Equipment,Hunan University of Technology,Zhuzhou Hunan 412007,China)
出处 《湖南工业大学学报》 2025年第1期26-34,共9页 Journal of Hunan University of Technology
基金 湖南省自然科学基金资助项目(2023JJ50193)。
关键词 永磁伺服电机 模型预测位置控制 滑模控制 负载转矩观测器 转动惯量辨识 permanent magnet servo motor model predictive position control sliding mode control load torque observer rotational inertia identification
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