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arXiv · 1912.07107

Optimal sensor scheduling under intermittent observations subject to network dynamics

Hassan Hmedi·Johnson Carroll·Ari Arapostathis
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Abstract

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, significantly extending earlier results on intermittent observations.

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Hassan Hmedi, Johnson Carroll, Ari Arapostathis. 2019-12-15. Optimal sensor scheduling under intermittent observations subject to network dynamics. https://arxiv.org/abs/1912.07107

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