9,677 research outputs found
Kalman Filtering With Relays Over Wireless Fading Channels
This note studies the use of relays to improve the performance of Kalman
filtering over packet dropping links. Packet reception probabilities are
governed by time-varying fading channel gains, and the sensor and relay
transmit powers. We consider situations with multiple sensors and relays, where
each relay can either forward one of the sensors' measurements to the
gateway/fusion center, or perform a simple linear network coding operation on
some of the sensor measurements. Using an expected error covariance performance
measure, we consider optimal and suboptimal methods for finding the best relay
configuration, and power control problems for optimizing the Kalman filter
performance. Our methods show that significant performance gains can be
obtained through the use of relays, network coding and power control, with at
least 30-40 less power consumption for a given expected error covariance
specification.Comment: 7 page
Optimal Energy Allocation for Kalman Filtering over Packet Dropping Links with Imperfect Acknowledgments and Energy Harvesting Constraints
This paper presents a design methodology for optimal transmission energy
allocation at a sensor equipped with energy harvesting technology for remote
state estimation of linear stochastic dynamical systems. In this framework, the
sensor measurements as noisy versions of the system states are sent to the
receiver over a packet dropping communication channel. The packet dropout
probabilities of the channel depend on both the sensor's transmission energies
and time varying wireless fading channel gains. The sensor has access to an
energy harvesting source which is an everlasting but unreliable energy source
compared to conventional batteries with fixed energy storages. The receiver
performs optimal state estimation with random packet dropouts to minimize the
estimation error covariances based on received measurements. The receiver also
sends packet receipt acknowledgments to the sensor via an erroneous feedback
communication channel which is itself packet dropping.
The objective is to design optimal transmission energy allocation at the
energy harvesting sensor to minimize either a finite-time horizon sum or a long
term average (infinite-time horizon) of the trace of the expected estimation
error covariance of the receiver's Kalman filter. These problems are formulated
as Markov decision processes with imperfect state information. The optimal
transmission energy allocation policies are obtained by the use of dynamic
programming techniques. Using the concept of submodularity, the structure of
the optimal transmission energy policies are studied. Suboptimal solutions are
also discussed which are far less computationally intensive than optimal
solutions. Numerical simulation results are presented illustrating the
performance of the energy allocation algorithms.Comment: Submitted to IEEE Transactions on Automatic Control. arXiv admin
note: text overlap with arXiv:1402.663
Circumferential pressure distributions in a model labyrinth seal
A research program to isolate and study leakage flow through labyrinth glands was initiated. Circumferential pressure distributions were measured in the labyrinth glands with geometry appropriate to the high pressure labyrinths in large steam turbines. Knowledge of this pressure distribution is essential as it is this unequal pressure field that results in the destabilizing force. Parameters that are likely to affect the pressure distributions are incorporated into the test rig. Some preliminary pressure profiles are presented
Game-Theoretic Pricing and Selection with Fading Channels
We consider pricing and selection with fading channels in a Stackelberg game
framework. A channel server decides the channel prices and a client chooses
which channel to use based on the remote estimation quality. We prove the
existence of an optimal deterministic and Markovian policy for the client, and
show that the optimal policies of both the server and the client have threshold
structures when the time horizon is finite. Value iteration algorithm is
applied to obtain the optimal solutions for both the server and client, and
numerical simulations and examples are given to demonstrate the developed
result.Comment: 6 pages, 4 figures, accepted by the 2017 Asian Control Conferenc
An Optimal Transmission Strategy for Kalman Filtering over Packet Dropping Links with Imperfect Acknowledgements
This paper presents a novel design methodology for optimal transmission
policies at a smart sensor to remotely estimate the state of a stable linear
stochastic dynamical system. The sensor makes measurements of the process and
forms estimates of the state using a local Kalman filter. The sensor transmits
quantized information over a packet dropping link to the remote receiver. The
receiver sends packet receipt acknowledgments back to the sensor via an
erroneous feedback communication channel which is itself packet dropping. The
key novelty of this formulation is that the smart sensor decides, at each
discrete time instant, whether to transmit a quantized version of either its
local state estimate or its local innovation. The objective is to design
optimal transmission policies in order to minimize a long term average cost
function as a convex combination of the receiver's expected estimation error
covariance and the energy needed to transmit the packets. The optimal
transmission policy is obtained by the use of dynamic programming techniques.
Using the concept of submodularity, the optimality of a threshold policy in the
case of scalar systems with perfect packet receipt acknowledgments is proved.
Suboptimal solutions and their structural results are also discussed. Numerical
results are presented illustrating the performance of the optimal and
suboptimal transmission policies.Comment: Conditionally accepted in IEEE Transactions on Control of Network
System
Non-Fundamental Expectations and Economic Fluctuations: Evidence from Professional Forecasts
It is theoretically possible that non-fundamental idiosyncratic shocks to agents’ rational expectations are a source of economic fluctuations. Studies using data on consumer and investor sentiment suggest that this is indeed a significant source of fluctuations. We present the results of a study that uses forecasts from professional forecasters to extract non-fundamental shocks to expectations. In contrast to previous studies, we show that non-fundamental expectations are not a significant source of output fluctuations.Non-fundamental expectations; Sunspots; Economic fluctuations; Survey of Professional Forecasters; Vector autoregressions
Experimental investigation of lateral forces induced by flow through model labyrinth glands
The lateral forces induced by flow through model labyrinth glands were investigated. Circumferential pressure distributions, lateral forces and stiffness coefficients data obtained are discussed. The force system is represented as a negative spring and a tangential force orthogonal to eccentricity. The magnitude of these forces are dependent on eccentricity, entry swirl, rotor peripheral velocity and seal size. A pressure equalization chamber at midgland tests should in significantly reduced forces and stiffness coefficients
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