对于可控励磁磁悬浮直线同步电机(CEMLLSM)，常规迭代学习控制(ILC)精度低、抖振大，且抗外部扰动能力差。为提高跟踪精度，设计了一种基于扩张状态观测器(ESO)的变增益自适应ILC算法。首先，研究CEMLLSM的工作原理及数学模型。其次，设计基于ESO的变增益自适应迭代学习控制器，为控制器中固定增益部分引入指数可变增益，增加自适应迭代项对控制律中的未知参数进行迭代学习，从而减小系统抖振与误差并加快系统收敛速度。通过引入ESO观测系统的外部干扰，对控制量进行补偿，进而提高系统的抗扰动能力。最后，用MATLAB对控制系统进行仿真分析，仿真结果表明该算法能够有效减小跟踪误差，并对扰动有良好的抑制作用。

For the controllable excitation magnetic levitation linear synchronous motor (CEMLLSM), the conventional iterative learning control (ILC) has low precision, large chattering and poor resistance to external disturbances. In order to improve the tracking accuracy, a variable gain adaptive ILC algorithm based on extended state observer (ESO) is designed. Firstly, the working principle and mathematical model of the CEMLLSM are studied. Secondly, a variable gain adaptive iterative learning controller based on ESO is designed. An exponential variable gain is introduced to the fixed gain part of the controller, and an adaptive iterative term is added to iteratively learn the unknown parameters in the control law, which reduces the chattering and error of the system, and speeds up the system convergence speed. By adding ESO, the external disturbance of system can be observed, and the control quantity is compensated to enhance the anti-disturbance performance of the system. Finally, the control system is simulated and analyzed with MATLAB, and the results show that the algorithm can successfully reduce tracking error and has a good suppression impact on disturbance.

国家自然科学基金项目（51575363）