Research Article

Process Noise Source Localization Using Kalman Filter

Volume: 1 Number: 2 December 21, 2020
Yalçın Bulut *, Barış Ünal
PDF Download
Journal of Science, Technology and Engineering Research Cover Journal of Science, Technology and Engineering Research
TR EN

Process Noise Source Localization Using Kalman Filter

Abstract

Due to complexity in the systems, spatial distribution of unmeasured process noise that is required for the controller and observer design are often unknown. In this study an innovations correlations approach developed in Kalman Filter theory is used to localize the process noise from output measurements. The approach calculates covariance matrices from analysis of resulting innovations from an arbitrary filter gain. Aim of this paper is to review the innovation correlations approach and to evaluate its performance for localization of the process noise. Numerical results suggest that the method can be effectively used for source localization of process noise as well as estimation of noise covariance matrices.

Keywords

Disturbance Localization , Kalman Filter , Measurement Noise , Process Noise , Process Noise Localization

References

  1. [1] Kalman R. E. “A new approach to linear filtering and prediction problems.” ASME Journal of Basic Engineering, 82:35-45, 1960.
  2. [2] Mehra, R. K. “On the identification of variance and adaptive Kalman filtering.” IEEE Transactions on Automatic Control, 15:175-184, 1970.
  3. [3] Carew B. and Belanger P. R . “Identification of Optimum Filter Steady-State Gain for Systems with Unknown Noise Covariances.” IEEE Transactions on Automatic Control, 18:582-587, 1974.
  4. [4] Neethling C. and Young P. “Comments on identification of optimum filter steady-state gain for systems with unknown noise covariances.” IEEE Transactions on Automatic Control, 19:623-625, 1974.
  5. [5] Odelson B. J. and Rajamani M. R. and Rawlings J. B. “A new autocovariance least-squares method for estimating noise covariances.” Automatica, 42(2):303-308, February 2006.
  6. [6] Akesson B. M. and Jùrgensen J. B. and Poulsen N. K. and Jùrgensen S. B . “A generalized autoco-variance least-squares method for Kalman filter tuning.” Journal of Process Control, 42(2), June 2007.
  7. [7] Bulut Y. and Vines-Cavanaugh D. and Bernal D. “Process and Measurement Noise Estimation for Kalman Filtering.” IMAC XXVIII, A Conference and Exposition on Structural Dynamics, February, 2010.

Details

Primary Language

English

Subjects

Automation Engineering

Journal Section

Research Article

Authors

Barış Ünal This is me
0000-0001-7038-1206
Türkiye

Publication Date

December 21, 2020

Submission Date

June 25, 2020

Acceptance Date

September 24, 2020

Published in Issue

Year 2020 Volume: 1 Number: 2

DOI

https://doi.org/10.5281/zenodo.4048219

IZ

https://izlik.org/JA74MD84JU

Cite

RIS / Bibtex
IEEE
[1]Y. Bulut and B. Ünal, “Process Noise Source Localization Using Kalman Filter”, Journal of Science, Technology and Engineering Research, vol. 1, no. 2, pp. 19–24, Dec. 2020, doi: 10.5281/zenodo.4048219.

Studies published in the journal are licensed under a

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0) International License. 

by-nc-nd.png

Free counters!