12,107 research outputs found
Decoding the `Nature Encoded' Messages for Distributed Energy Generation Control in Microgrid
The communication for the control of distributed energy generation (DEG) in
microgrid is discussed. Due to the requirement of realtime transmission, weak
or no explicit channel coding is used for the message of system state. To
protect the reliability of the uncoded or weakly encoded messages, the system
dynamics are considered as a `nature encoding' similar to convolution code, due
to its redundancy in time. For systems with or without explicit channel coding,
two decoding procedures based on Kalman filtering and Pearl's Belief
Propagation, in a similar manner to Turbo processing in traditional data
communication systems, are proposed. Numerical simulations have demonstrated
the validity of the schemes, using a linear model of electric generator dynamic
system.Comment: It has been submitted to IEEE International Conference on
Communications (ICC
Optimal LQG Control Across a Packet-Dropping Link
We examine optimal Linear Quadratic Gaussian control for a system in which communication between the sensor (output of the plant) and the controller occurs across a packet-dropping link. We extend the familiar LQG separation principle to this problem that allows us to solve this problem using a standard LQR state-feedback design, along with an optimal algorithm for propagating and using the information across the unreliable link. We present one such optimal algorithm, which consists of a Kalman Filter at the sensor side of the link, and a switched linear filter at the controller side. Our design does not assume any statistical model of the packet drop events, and is thus optimal for an arbitrary packet drop pattern. Further, the solution is appealing from a practical point of view because it can be implemented as a small modification of an existing LQG control design
Prochlo: Strong Privacy for Analytics in the Crowd
The large-scale monitoring of computer users' software activities has become
commonplace, e.g., for application telemetry, error reporting, or demographic
profiling. This paper describes a principled systems architecture---Encode,
Shuffle, Analyze (ESA)---for performing such monitoring with high utility while
also protecting user privacy. The ESA design, and its Prochlo implementation,
are informed by our practical experiences with an existing, large deployment of
privacy-preserving software monitoring.
(cont.; see the paper
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Sparse Packetized Predictive Control for Networked Control over Erasure Channels
We study feedback control over erasure channels with packet-dropouts. To
achieve robustness with respect to packet-dropouts, the controller transmits
data packets containing plant input predictions, which minimize a finite
horizon cost function. To reduce the data size of packets, we propose to adopt
sparsity-promoting optimizations, namely, ell-1-ell-2 and ell-2-constrained
ell-0 optimizations, for which efficient algorithms exist. We derive sufficient
conditions on design parameters, which guarantee (practical) stability of the
resulting feedback control systems when the number of consecutive
packet-dropouts is bounded.Comment: IEEE Transactions on Automatic Control, Volume 59 (2014), Issue 7
(July) (to appear
Error Correcting Codes for Distributed Control
The problem of stabilizing an unstable plant over a noisy communication link
is an increasingly important one that arises in applications of networked
control systems. Although the work of Schulman and Sahai over the past two
decades, and their development of the notions of "tree codes"\phantom{} and
"anytime capacity", provides the theoretical framework for studying such
problems, there has been scant practical progress in this area because explicit
constructions of tree codes with efficient encoding and decoding did not exist.
To stabilize an unstable plant driven by bounded noise over a noisy channel one
needs real-time encoding and real-time decoding and a reliability which
increases exponentially with decoding delay, which is what tree codes
guarantee. We prove that linear tree codes occur with high probability and, for
erasure channels, give an explicit construction with an expected decoding
complexity that is constant per time instant. We give novel sufficient
conditions on the rate and reliability required of the tree codes to stabilize
vector plants and argue that they are asymptotically tight. This work takes an
important step towards controlling plants over noisy channels, and we
demonstrate the efficacy of the method through several examples.Comment: 39 page
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