Electronic Infromation School, Wuhan University, Wuhan 430070, China.
Sensors (Basel). 2022 Jun 3;22(11):4270. doi: 10.3390/s22114270.
The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area.
磁悬浮系统已被认为是微加工领域中一种很有前途的执行器。为了提高磁悬浮转台的跟踪性能和抗扰能力,提出了一种具有干扰补偿的迭代学习 PID 控制策略。估计的干扰补偿控制信号,以提高主动抗扰能力。迭代学习控制用作前馈单元,进一步减小轨迹跟踪误差。分析了具有干扰补偿的迭代学习 PID 的收敛性和稳定性。在内部定制的磁悬浮转台上进行了一系列对比实验,实验结果突出了所提出控制策略的优越性。具有干扰补偿的迭代学习 PID 使磁悬浮转台能够在复杂的外部干扰下实现良好的跟踪性能。所提出的控制策略增强了磁悬浮系统在机构制造领域的适用性。