632 research outputs found
Stabilization over power-constrained parallel Gaussian channels
This technical note is concerned with state-feedback stabilization of multi-input systems over parallel Gaussian channels subject to a total power constraint. Both continuous-time and discrete-time systems are treated under the framework of H2 control, and necessary/sufficient conditions for stabilizability are established in terms of inequalities involving unstable plant poles, transmitted power, and noise variances. These results are further used to clarify the relationship between channel capacity and stabilizability. Compared to single-input systems, a range of technical issues arise. In particular, in the multi-input case, the optimal controller has a separation structure, and the lower bound on channel capacity for some discrete-time systems is unachievable by linear time-invariant (LTI) encoders/decoder
Mean Square Capacity of Power Constrained Fading Channels with Causal Encoders and Decoders
This paper is concerned with the mean square stabilization problem of
discrete-time LTI systems over a power constrained fading channel. Different
from existing research works, the channel considered in this paper suffers from
both fading and additive noises. We allow any form of causal channel
encoders/decoders, unlike linear encoders/decoders commonly studied in the
literature. Sufficient conditions and necessary conditions for the mean square
stabilizability are given in terms of channel parameters such as transmission
power and fading and additive noise statistics in relation to the unstable
eigenvalues of the open-loop system matrix. The corresponding mean square
capacity of the power constrained fading channel under causal encoders/decoders
is given. It is proved that this mean square capacity is smaller than the
corresponding Shannon channel capacity. In the end, numerical examples are
presented, which demonstrate that the causal encoders/decoders render less
restrictive stabilizability conditions than those under linear
encoders/decoders studied in the existing works.Comment: Accepted by the 54th IEEE Conference on Decision and Contro
Stabilization of systems with asynchronous sensors and controllers
We study the stabilization of networked control systems with asynchronous
sensors and controllers. Offsets between the sensor and controller clocks are
unknown and modeled as parametric uncertainty. First we consider multi-input
linear systems and provide a sufficient condition for the existence of linear
time-invariant controllers that are capable of stabilizing the closed-loop
system for every clock offset in a given range of admissible values. For
first-order systems, we next obtain the maximum length of the offset range for
which the system can be stabilized by a single controller. Finally, this bound
is compared with the offset bounds that would be allowed if we restricted our
attention to static output feedback controllers.Comment: 32 pages, 6 figures. This paper was partially presented at the 2015
American Control Conference, July 1-3, 2015, the US
Input-output stabilization of linear systems on Z
A formal framework is set up for the discussion of generalized autoregressive with external input models of the form Ay__Bu, where A and B are linear operators, with the main emphasis being on signal spaces consisting of bounded sequences parametrized by the integers. Different notions of stability are explored, and topological notions such as the idea of a closed system are linked with questions of stabilizability in this very general context. Various problems inherent in using Z as the time axis are analyzed in this operatorial framework
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