多目标遗传算法在波荡器垫补中的应用

波荡器性能一般有多个指标要求，而这些指标往往是相互冲突的，因此在磁场垫补时难以对垫补量进行精确推算，导致磁场垫补耗时和低效。为解决该问题，本文将多目标遗传算法应用于波荡器磁场垫补量推算，并对波荡器U38-S磁场进行了垫补。根据波荡器磁场垫补结构建立了计算模型，并阐述了计算模型中的主要问题，给出了U38-S磁场的垫补过程。经过3次磁场垫补，U38-S的轨迹中心偏差、相位误差和峰峰值误差分别减小到0.15 mm、1°和0.49%。由于遗传算法本身具有较强的可扩展性，本文所用方法也可应用于其他类型波荡器的磁场垫补。

Application of Multi-objective Genetic Algorithm on Undulator Shimming

The performances of undulator generally have multiple specification requirements, which are often conflicting. It is difficult to accurately estimate the shimming at magnetic field shimming, resulting in time consuming and inefficiency. In order to solve the problem, in this paper a multi-objective genetic algorithm was applied to calculate the shimming of undulator magnetic field, and the magnetic field shimming of the undulator U38-S was finished. The calculation model was set up according to the shimming structure and the main problems in the calculation model were expounded. At last, the magnetic field shimming process of U38-S was given. After three times of magnetic field shimming, the trajectory center deviation, phase error and peak-to-peak error of U38-S are reduced to 0.15 mm, 1° and 0.49%, respectively. Besides, because of the strong expansibility of the genetic algorithm, the method used in this paper can also be applied to the magnetic field shimming of other types of undulators.