This paper studies strategic design in an integrated sensing and communication (ISAC) architecture for feedback control of cyber-physical systems. We focus on a setting in which the regulation of a physical process (i.e., remote source) is performed via an ISAC-enabled base station. The base station can alternate between tracking the state of the source and delivering control-relevant information back to the source. For a Gauss-Markov source subject to i.i.d. Bernoulli sensing and communication links, under a finite-horizon linear-quadratic-Gaussian cost, we rigorously characterise the optimal policies through an uncertainty-aware synthesis. We establish that the optimal switching policy, for the ISAC system at the base station, is threshold-based in terms of the source and base-station estimation covariances, while the optimal control policy, for the actuator at the source, is linear in the source state estimate. We show that the threshold region$\unicode{x2014}$defined as the set of estimation covariance pairs for which communication is preferred over sensing$\unicode{x2014}$expands with increasing source uncertainty and contracts with increasing base-station uncertainty.

翻译：本文研究面向信息物理系统反馈控制的集成感知与通信（ISAC）架构中的策略设计。我们聚焦于通过支持ISAC的基站对物理过程（即远程信源）进行调控的场景。该基站可在追踪信源状态与向信源回传控制相关信息两种模式间切换。针对受独立同分布伯努利感知与通信链路影响的高斯-马尔可夫信源，在有限时域线性二次高斯代价函数下，我们通过不确定性感知的综合方法严格刻画了最优策略。我们证明：基站处ISAC系统的最优切换策略在信源与基站估计协方差方面具有阈值特性；而信源处执行器的最优控制策略在信源状态估计上呈线性关系。研究表明：阈值区域——即倾向于通信而非感知的估计协方差对集合——随信源不确定性的增加而扩展，并随基站不确定性的增加而收缩。