论文标题
在对部分观察到的不确定系统的强大控制下，添加成本
On Robust Control of Partially Observed Uncertain Systems with Additive Costs
论文作者
论文摘要
在本文中，我们考虑了优化部分观察到的系统最坏情况行为的问题。所有不受控制的干扰均被建模为有限价值的不确定变量。使用成本分布理论，我们提出了一种动态编程（DP）方法来计算控制策略，该策略可最大程度地减少给定时间范围内最大可能的总成本。为了提高最佳DP的计算效率，我们介绍了信息状态的一般定义，并表明以前研究工作中构建的许多信息状态都是我们的特殊情况。此外，我们定义了近似信息状态和近似DP，可以通过承认有限的性能损失来进一步改善计算障碍。我们使用数值示例说明了这些结果的实用性。
In this paper, we consider the problem of optimizing the worst-case behavior of a partially observed system. All uncontrolled disturbances are modeled as finite-valued uncertain variables. Using the theory of cost distributions, we present a dynamic programming (DP) approach to compute a control strategy that minimizes the maximum possible total cost over a given time horizon. To improve the computational efficiency of the optimal DP, we introduce a general definition for information states and show that many information states constructed in previous research efforts are special cases of ours. Additionally, we define approximate information states and an approximate DP that can further improve computational tractability by conceding a bounded performance loss. We illustrate the utility of these results using a numerical example.
