论文标题
Wasserstein对部分可观察的线性系统的分布可靠地控制：可拖动的近似和性能保证
Wasserstein Distributionally Robust Control of Partially Observable Linear Systems: Tractable Approximation and Performance Guarantee
论文作者
论文摘要
Wasserstein分布在稳健的控制（WDRC）是一种解决随机系统干扰的分布信息的有效方法。它提供了各种显着功能，例如样本外的性能保证，而大多数现有方法都使用全州观测值。在本文中，我们开发了一种计算障碍的WDRC方法，用于离散时间部分可观察到的线性季度（LQ）控制问题。关键思想是将WDRC问题重新制定为新型的最小值控制问题，并进行了近似沃斯坦的惩罚。我们使用非平凡的riccati方程来得出近似问题的最佳控制策略的封闭式表达。我们进一步显示了由此产生的控制器的保证成本属性，并确定了最佳差距的可证明的约束。最后，我们通过使用高斯和非高斯干扰来评估方法的性能。
Wasserstein distributionally robust control (WDRC) is an effective method for addressing inaccurate distribution information about disturbances in stochastic systems. It provides various salient features, such as an out-of-sample performance guarantee, while most of the existing methods use full-state observations. In this paper, we develop a computationally tractable WDRC method for discrete-time partially observable linear-quadratic (LQ) control problems. The key idea is to reformulate the WDRC problem as a novel minimax control problem with an approximate Wasserstein penalty. We derive a closed-form expression of the optimal control policy of the approximate problem using a nontrivial Riccati equation. We further show the guaranteed cost property of the resulting controller and identify a provable bound for the optimality gap. Finally, we evaluate the performance of our method through numerical experiments using both Gaussian and non-Gaussian disturbances.
