论文标题
用于光学应用中动态极化控制的Jacobian方法
Jacobian Methods for Dynamic Polarization Control in Optical Applications
论文作者
论文摘要
动态极化控制（DPC）对许多光学应用都是有益的。它使用可调节的波形来执行自动极化跟踪和操作。有效的算法对于在高速下实现无尽的极化控制过程至关重要。但是，基于标准梯度的算法尚未很好地分析。在这里，我们使用基于雅各布的控制理论框架对DPC进行建模，该框架与机器人运动学有很多共同点。然后，我们详细分析了Stokes矢量梯度作为Jacobian矩阵的状况。我们将多阶段DPC识别为一个冗余系统，启用具有空空间操作的控制算法。可以找到一种有效的，无复位的算法。我们预计会有更多定制的DPC算法将在各种光学系统中遵循相同的框架。
Dynamic polarization control (DPC) is beneficial for many optical applications. It uses adjustable waveplates to perform automatic polarization tracking and manipulation. Efficient algorithms are essential to realizing an endless polarization control process at high speed. However, the standard gradientbased algorithm is not well analyzed. Here we model the DPC with a Jacobian-based control theory framework that finds a lot in common with robot kinematics. We then give a detailed analysis of the condition of the Stokes vector gradient as a Jacobian matrix. We identify the multi-stage DPC as a redundant system enabling control algorithms with null-space operations. An efficient, reset-free algorithm can be found. We anticipate more customized DPC algorithms to follow the same framework in various optical systems.
