论文标题
一种补偿加速器性能漂移的优化方法
An optimization method to compensate accelerator performance drifts
论文作者
论文摘要
由于机器组件或周围环境的世俗变化，加速器性能通常会随着时间的流逝而随着时间的流逝而恶化。在许多情况下，一些调整旋钮可有效补偿性能漂移，并且可以使用优化方法来找到理想的机器设置。但是，这种干预通常不能在不中断用户操作的情况下进行，因为优化算法会大大影响机器性能。我们提出了一种优化算法，安全的稳健共轭方向搜索（RCDS-S），可以执行加速器调整，同时将机器性能保持在指定的安全信封内。该算法使用函数的Lipschitz连续性以及漂移的特征构建了目标函数的概率模型，并适用于选择试验解决方案，以确保机器在调谐过程中安全地运行。该算法可以在正常用户操作期间或定期运行期间运行，以补偿性能漂移。已经进行了模拟和在线测试来验证算法的性能。
Accelerator performance often deteriorates with time during a long period of operation due to secular changes in the machine components or the surrounding environment. In many cases some tuning knobs are effective in compensating the performance drifts and optimization methods can be used to find the ideal machine setting. However, such intervention usually cannot be done without interrupting user operation as the optimization algorithms can substantially impact the machine performance. We propose an optimization algorithm, Safe Robust Conjugate Direction Search (RCDS-S), which can perform accelerator tuning while keeping the machine performance within a designated safe envelope. The algorithm builds probability models of the objective function using Lipschitz continuity of the function as well as characteristics of the drifts and applies to the selection of trial solutions to ensure the machine operates safely during tuning. The algorithm can run during normal user operation constantly, or periodically, to compensate the performance drifts. Simulation and online tests have been done to validate the performance of the algorithm.
