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.
翻译:动态极化控制(DPC) 有益于许多光学应用。 它使用可调整的波板进行自动极化跟踪和操纵。 高效算法对于高速实现无休止的极化控制进程至关重要。 但是, 标准梯度算法没有很好地分析。 我们在这里用一个基于雅各布的控制理论框架来模拟DPC, 这个框架与机器人的动脉学有许多共同之处。 然后我们详细分析斯托克斯矢量梯度作为雅各矩阵的状态。 我们确定多阶段的DPC是一个冗余系统, 使无空间操作的控制算法得以进行。 可以找到一个高效的、 重设自由的算法。 我们预计, 更定制的DPC 算法可以在各种光学系统中遵循相同的框架 。