Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Event-Based State Estimation Using an Improved Stochastic Send-on-Delta Sampling Scheme

Thelander Andrén, Marcus LU and Cervin, Anton LU orcid (2016) Event-Based Control, Communication and Signal Processing 2016
Abstract
Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applications found in e.g. networked control systems. Recently, stochastic event-triggering rules have been proposed as a means to avoid the complexity of the problem that normally arises in event-based estimator design. By using a scaled Gaussian function in the stochastic triggering scheme, the optimal remote state estimator becomes a linear Kalman filter with a case dependent measurement update. In this paper we propose a modified version of the stochastic send-on-delta triggering rule. The idea is to use a very simple predictor in the sensor, which allows the communication rate to be reduced while... (More)
Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applications found in e.g. networked control systems. Recently, stochastic event-triggering rules have been proposed as a means to avoid the complexity of the problem that normally arises in event-based estimator design. By using a scaled Gaussian function in the stochastic triggering scheme, the optimal remote state estimator becomes a linear Kalman filter with a case dependent measurement update. In this paper we propose a modified version of the stochastic send-on-delta triggering rule. The idea is to use a very simple predictor in the sensor, which allows the communication rate to be reduced while preserving estimation performance compared to regular stochastic send-on-delta sampling. We derive the optimal mean-square error estimator for the new scheme and present upper and lower bounds on the error covariance. The proposed scheme is evaluated in numerical examples, where it compares favorably to previous stochastic sampling approaches, and is shown to preserve estimation performance well even at large reductions in communication rate. (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
remote state estimator, stochastic triggering, send-on-delta sampling, minimal mean square error estimator, event-based estimation
host publication
2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)
pages
8 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
Event-Based Control, Communication and Signal Processing 2016
conference location
Kraków, Poland
conference dates
2016-06-13 - 2016-06-15
external identifiers
  • scopus:84998704823
  • wos:000386662400015
ISBN
978-1-5090-4196-1
DOI
10.1109/EBCCSP.2016.7605237
project
ELLIIT LU P02: Co-Design of Robust and Secure Networked Embedded Control Systems
Event-Based Control of Stochastic Systems with Application to Server Systems
language
English
LU publication?
yes
id
01d94738-9c3b-47d3-b020-a851ad2b8fd4
date added to LUP
2016-08-15 14:40:11
date last changed
2024-02-03 07:17:38
@inproceedings{01d94738-9c3b-47d3-b020-a851ad2b8fd4,
  abstract     = {{Event-based sensing and communication holds the promise of lower resource utilization and/or better performance for remote state estimation applications found in e.g. networked control systems. Recently, stochastic event-triggering rules have been proposed as a means to avoid the complexity of the problem that normally arises in event-based estimator design. By using a scaled Gaussian function in the stochastic triggering scheme, the optimal remote state estimator becomes a linear Kalman filter with a case dependent measurement update. In this paper we propose a modified version of the stochastic send-on-delta triggering rule. The idea is to use a very simple predictor in the sensor, which allows the communication rate to be reduced while preserving estimation performance compared to regular stochastic send-on-delta sampling. We derive the optimal mean-square error estimator for the new scheme and present upper and lower bounds on the error covariance. The proposed scheme is evaluated in numerical examples, where it compares favorably to previous stochastic sampling approaches, and is shown to preserve estimation performance well even at large reductions in communication rate.}},
  author       = {{Thelander Andrén, Marcus and Cervin, Anton}},
  booktitle    = {{2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)}},
  isbn         = {{978-1-5090-4196-1}},
  keywords     = {{remote state estimator; stochastic triggering; send-on-delta sampling; minimal mean square error estimator; event-based estimation}},
  language     = {{eng}},
  month        = {{06}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Event-Based State Estimation Using an Improved Stochastic Send-on-Delta Sampling Scheme}},
  url          = {{https://lup.lub.lu.se/search/files/18480516/EBCCSP_2016_submission_22.pdf}},
  doi          = {{10.1109/EBCCSP.2016.7605237}},
  year         = {{2016}},
}