Opportunistic Control Over Shared Wireless Channels
Abstract
© 2015 IEEE.We consider a wireless control architecture with multiple control loops
over a shared wireless medium. A scheduler observes the random channel conditions
that each control system experiences over the shared medium and opportunistically
selects systems to transmit at a set of non-overlapping frequencies. The transmit
power of each system also adapts to channel conditions and determines the probability
of successfully receiving and closing the loop. We formulate the optimal design of
channel-aware scheduling and power allocation that minimize the total power consumption
while meeting control performance requirements for all systems. In particular, it
is required that for each control system a given Lyapunov function decreases at a
specified rate in expectation over the random channel conditions. We develop an offline
algorithm to find the optimal communication design, as well as an online protocol
which selects scheduling and power variables based on a random observed channel sequence
and converges almost surely to the optimal operating point. Simulations illustrate
the power savings of our approach compared to other non-channel-aware schemes.
Type
Journal articlePermalink
https://hdl.handle.net/10161/10335Published Version (Please cite this version)
10.1109/TAC.2015.2416922Publication Info
Gatsis, K; Pajic, M; Ribeiro, A; & Pappas, GJ (2015). Opportunistic Control Over Shared Wireless Channels. IEEE Transactions on Automatic Control, 60(12). pp. 3140-3155. 10.1109/TAC.2015.2416922. Retrieved from https://hdl.handle.net/10161/10335.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Miroslav Pajic
Dickinson Family Associate Professor
Miroslav Pajic's research focuses on design and analysis of cyber-physical systems
with varying levels of autonomy and human interaction, at the intersection of (more
traditional) areas of embedded systems, AI, learning and controls, formal methods
and robotics.

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