The Ensemble Kalman Filter method can be used as an iterative particle numerical scheme for state dynamics estimation and control--to--observable identification problems. In applications it may be required to enforce the solution to satisfy equality constraints on the control space. In this work we deal with this problem from a constrained optimization point of view, deriving corresponding optimality conditions. Continuous limits, in time and in the number of particles, allows us to study properties of the method. We illustrate the performance of the method by using test inverse problems from the literature.

中文翻译：

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约束集成卡尔曼滤波器的连续极限

集成卡尔曼滤波器方法可用作状态动力学估计和控制到可观察识别问题的迭代粒子数值方案。在应用程序中，可能需要强制执行解决方案以满足控制空间上的等式约束。在这项工作中，我们从约束优化的角度处理这个问题，推导出相应的最优条件。在时间和粒子数量方面的连续限制使我们能够研究该方法的特性。我们通过使用文献中的测试逆问题来说明该方法的性能。