Abstract In this paper, we propose an optimization-based design technique for constrained control and bounded-error state estimation for affine systems in the presence of intermittent measurements. We treat the affine system as a switched system where the measurement equation switches between two modes based on whether a measurement exists or is missing, and model potential missing data patterns with a finite-length language that constrains the feasible mode sequences. Then, we introduce a novel property, equalized recovery, that generalizes the equalized performance property and that allows us to tolerate missing observations. By utilizing Q -parametrization, we show that a finite horizon optimal estimator/controller can be constructed using time-based and prefix-based approaches, where the latter implicitly estimates the specific missing data pattern (i.e., mode sequence), within the given language, according to the prefix observed so far. We illustrate with numerical examples that the proposed approaches can provide desirable performance guarantees.

中文翻译：

---

存在缺失数据时的有限视界约束控制和有界误差估计

摘要 在本文中，我们提出了一种基于优化的设计技术，用于存在间歇测量的仿射系统的约束控制和有界误差状态估计。我们将仿射系统视为一个切换系统，其中测量方程根据测量是否存在或缺失在两种模式之间切换，并使用限制可行模式序列的有限长度语言对潜在的缺失数据模式进行建模。然后，我们引入了一个新的特性，均衡恢复，它概括了均衡性能特性，并允许我们容忍缺失的观察。通过利用 Q 参数化，我们表明可以使用基于时间和基于前缀的方法构建有限范围最优估计器/控制器，其中后者根据目前观察到的前缀隐式估计给定语言内的特定缺失数据模式（即模式序列）。我们用数值例子说明所提出的方法可以提供理想的性能保证。