745 research outputs found
Stabilization of Linear Systems Over Gaussian Networks
The problem of remotely stabilizing a noisy linear time invariant plant over
a Gaussian relay network is addressed. The network is comprised of a sensor
node, a group of relay nodes and a remote controller. The sensor and the relay
nodes operate subject to an average transmit power constraint and they can
cooperate to communicate the observations of the plant's state to the remote
controller. The communication links between all nodes are modeled as Gaussian
channels. Necessary as well as sufficient conditions for mean-square
stabilization over various network topologies are derived. The sufficient
conditions are in general obtained using delay-free linear policies and the
necessary conditions are obtained using information theoretic tools. Different
settings where linear policies are optimal, asymptotically optimal (in certain
parameters of the system) and suboptimal have been identified. For the case
with noisy multi-dimensional sources controlled over scalar channels, it is
shown that linear time varying policies lead to minimum capacity requirements,
meeting the fundamental lower bound. For the case with noiseless sources and
parallel channels, non-linear policies which meet the lower bound have been
identified
Stabilizability of Markov jump linear systems modeling wireless networked control scenarios (extended version)
The communication channels used to convey information between the components
of wireless networked control systems (WNCSs) are subject to packet losses due
to time-varying fading and interference. The WNCSs with missing packets can be
modeled as Markov jump linear systems with one time-step delayed mode
observations. While the problem of the optimal linear quadratic regulation for
such systems has been already solved, we derive the necessary and sufficient
conditions for stabilizability. We also show, with an example considering a
communication channel model based on WirelessHART (a on-the-market wireless
communication standard specifically designed for process automation), that such
conditions are essential to the analysis of WNCSs where packet losses are
modeled with Bernoulli random variables representing the expected value of the
real random process governing the channel.Comment: Extended version of the paper accepted for the presentation at the
58th IEEE Conference on Decision and Control (CDC 2019
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