Optimal Sensor Scheduling Under Intermittent Observations Subject to Network Dynamics

• 成果类型: Article
• 署名作者: Hmedi, Hassan; Carroll, Johnson; Arapostathis, Ari
• 署名单位: University of Texas System; University of Texas Austin; University of Johannesburg
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3151578
• 发表日期: 2023
• 页码: 1399-1414
• 关键词: Intermittent observations; linear quadratic Gaussian (LQG) control; Markov decision processes (MDPs); networked control systems; sensor scheduling

摘要

Motivated by various distributed control applications, we consider a linear system with Gaussian noise observed by multiple sensors which transmit measurements over a dynamic lossy network. We characterize the stationary optimal sensor scheduling policy for the finite horizon, discounted, and long-term average cost problems and show that the value iteration algorithm converges to a solution of the average cost problem. We further show that the suboptimal policies provided by the rolling horizon truncation of the value iteration also guarantee stability and provide near-optimal average cost. Lastly, we provide qualitative characterizations of the multidimensional set of measurement loss rates for which the system is stabilizable for a static network, thus extending earlier results on intermittent observations.