57,028 research outputs found
Performance bounds for optimal feedback control in networks
Many important complex networks, including critical infrastructure and
emerging industrial automation systems, are becoming increasingly intricate
webs of interacting feedback control loops. A fundamental concern is to
quantify the control properties and performance limitations of the network as a
function of its dynamical structure and control architecture. We study
performance bounds for networks in terms of optimal feedback control costs. We
provide a set of complementary bounds as a function of the system dynamics and
actuator structure. For unstable network dynamics, we characterize a tradeoff
between feedback control performance and the number of control inputs, in
particular showing that optimal cost can increase exponentially with the size
of the network. We also derive a bound on the performance of the worst-case
actuator subset for stable networks, providing insight into dynamics properties
that affect the potential efficacy of actuator selection. We illustrate our
results with numerical experiments that analyze performance in regular and
random networks
Stochastic Online Shortest Path Routing: The Value of Feedback
This paper studies online shortest path routing over multi-hop networks. Link
costs or delays are time-varying and modeled by independent and identically
distributed random processes, whose parameters are initially unknown. The
parameters, and hence the optimal path, can only be estimated by routing
packets through the network and observing the realized delays. Our aim is to
find a routing policy that minimizes the regret (the cumulative difference of
expected delay) between the path chosen by the policy and the unknown optimal
path. We formulate the problem as a combinatorial bandit optimization problem
and consider several scenarios that differ in where routing decisions are made
and in the information available when making the decisions. For each scenario,
we derive a tight asymptotic lower bound on the regret that has to be satisfied
by any online routing policy. These bounds help us to understand the
performance improvements we can expect when (i) taking routing decisions at
each hop rather than at the source only, and (ii) observing per-link delays
rather than end-to-end path delays. In particular, we show that (i) is of no
use while (ii) can have a spectacular impact. Three algorithms, with a
trade-off between computational complexity and performance, are proposed. The
regret upper bounds of these algorithms improve over those of the existing
algorithms, and they significantly outperform state-of-the-art algorithms in
numerical experiments.Comment: 18 page
Coherence in Large-Scale Networks: Dimension-Dependent Limitations of Local Feedback
We consider distributed consensus and vehicular formation control problems.
Specifically we address the question of whether local feedback is sufficient to
maintain coherence in large-scale networks subject to stochastic disturbances.
We define macroscopic performance measures which are global quantities that
capture the notion of coherence; a notion of global order that quantifies how
closely the formation resembles a solid object. We consider how these measures
scale asymptotically with network size in the topologies of regular lattices in
1, 2 and higher dimensions, with vehicular platoons corresponding to the 1
dimensional case. A common phenomenon appears where a higher spatial dimension
implies a more favorable scaling of coherence measures, with a dimensions of 3
being necessary to achieve coherence in consensus and vehicular formations
under certain conditions. In particular, we show that it is impossible to have
large coherent one dimensional vehicular platoons with only local feedback. We
analyze these effects in terms of the underlying energetic modes of motion,
showing that they take the form of large temporal and spatial scales resulting
in an accordion-like motion of formations. A conclusion can be drawn that in
low spatial dimensions, local feedback is unable to regulate large-scale
disturbances, but it can in higher spatial dimensions. This phenomenon is
distinct from, and unrelated to string instability issues which are commonly
encountered in control problems for automated highways.Comment: To appear in IEEE Trans. Automat. Control; 15 pages, 2 figure
Power-Optimal Feedback-Based Random Spectrum Access for an Energy Harvesting Cognitive User
In this paper, we study and analyze cognitive radio networks in which
secondary users (SUs) are equipped with Energy Harvesting (EH) capability. We
design a random spectrum sensing and access protocol for the SU that exploits
the primary link's feedback and requires less average sensing time. Unlike
previous works proposed earlier in literature, we do not assume perfect
feedback. Instead, we take into account the more practical possibilities of
overhearing unreliable feedback signals and accommodate spectrum sensing
errors. Moreover, we assume an interference-based channel model where the
receivers are equipped with multi-packet reception (MPR) capability.
Furthermore, we perform power allocation at the SU with the objective of
maximizing the secondary throughput under constraints that maintain certain
quality-of-service (QoS) measures for the primary user (PU)
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