Optimal scheduling of multiple sensors which transmit measurements over a dynamic lossy network
Optimal scheduling of multiple sensors which transmit measurements over a dynamic lossy network
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DOI：
10.1109/cdc40024.2019.9029779
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
Johnson Carroll;Hassan Hmedi;A. Arapostathis
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文献类型：
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作者：
Johnson Carroll;Hassan Hmedi;A. Arapostathis
受各种分布式控制应用的启发，我们考虑了一个带有高斯噪声的线性系统，该系统由多个传感器观测，这些传感器在动态有损网络上传输测量数据。我们刻画了有限时间、折扣和长期平均费用问题的平稳最优传感器调度策略，并证明了数值迭代算法收敛于平均费用问题的解。我们进一步证明了由值迭代的滚动水平截断提供的次最优策略也保证几何遍历性和提供接近最优的平均代价。最后，我们给出了系统在静态网络中可镇定的多维测量丢失率集合的定性刻画，大大推广了早期关于间歇观测的结果。
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 geometric ergodicity 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, significantly extending earlier results on intermittent observations.