2,393 research outputs found
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
Space-Time Sampling for Network Observability
Designing sparse sampling strategies is one of the important components in
having resilient estimation and control in networked systems as they make
network design problems more cost-effective due to their reduced sampling
requirements and less fragile to where and when samples are collected. It is
shown that under what conditions taking coarse samples from a network will
contain the same amount of information as a more finer set of samples. Our goal
is to estimate initial condition of linear time-invariant networks using a set
of noisy measurements. The observability condition is reformulated as the frame
condition, where one can easily trace location and time stamps of each sample.
We compare estimation quality of various sampling strategies using estimation
measures, which depend on spectrum of the corresponding frame operators. Using
properties of the minimal polynomial of the state matrix, deterministic and
randomized methods are suggested to construct observability frames. Intrinsic
tradeoffs assert that collecting samples from fewer subsystems dictates taking
more samples (in average) per subsystem. Three scalable algorithms are
developed to generate sparse space-time sampling strategies with explicit error
bounds.Comment: Submitted to IEEE TAC (Revised Version
Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices
Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments;
where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range
estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in
delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both
ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient
signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution,
tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on
TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate
an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally,
we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible
acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance
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