Abstract
In this paper, we consider a mission-critical control system, where an unstable dynamic plant is monitored by a number of distributed sensors connected to the controller over the wireless fading channels. We focus on the dynamic sensor scheduling to stabilize the unstable dynamic plant. The dynamic sensor scheduling is modeled as a non-convex drift-plus-penalty minimization problem. To improve the scheduling efficiency, the proposed scheme adapts to both the fading channel state as well as the dynamic plant state. To overcome the non-convexity in the minimization problem, we propose a novel transformation technique for the scheduling variables and the objective function (using the Lyapunov drift). Based on that, we can derive a low complexity dynamic sensor scheduling scheme and also obtain a closed-form stability analysis (despite the non-convexity) of the mission-critical control system via a randomized state-independent policy. Compared with various baselines, the proposed scheme has higher power efficiency and superior scalability performance.
Published Version
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