An approximate minimum mean-square error estimator for linear discrete time-varying systems: Handling Try-Once-Discard protocol. (January 2023)
- Record Type:
- Journal Article
- Title:
- An approximate minimum mean-square error estimator for linear discrete time-varying systems: Handling Try-Once-Discard protocol. (January 2023)
- Main Title:
- An approximate minimum mean-square error estimator for linear discrete time-varying systems: Handling Try-Once-Discard protocol
- Authors:
- Liu, Qinyuan
Wang, Zidong
He, Xiao
Dong, Hongli
Jiang, Changjun - Abstract:
- Abstract: This paper is concerned with the remote state estimation problem for a class of linear discrete time-varying stochastic systems under communication constraints. In order to mitigate the undesired phenomena of data collisions, a Try-Once-Discard (TOD) protocol is utilized to regulate the signal transmissions over the sensor-to-estimator communication channel, where the TOD protocol is based on the scheduling rule described by a specific switching function. Under the introduced TOD protocol, the approximate minimum mean-square error (MMSE) state estimation problem is investigated and a recursive algorithm is developed for the MMSE estimator design whose computational complexity is comparable to that of the conventional Kalman filter. Furthermore, some conditions are established for the boundedness of the estimation error covariance. A numerical example is presented to illustrate the effectiveness of the proposed MMSE estimator.
- Is Part Of:
- Automatica. Volume 147(2023)
- Journal:
- Automatica
- Issue:
- Volume 147(2023)
- Issue Display:
- Volume 147, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 147
- Issue:
- 2023
- Issue Sort Value:
- 2023-0147-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-01
- Subjects:
- Networked systems -- Minimum mean-square error estimation -- Try-Once-Discard protocol -- Kalman filter -- Boundedness analysis
Automatic control -- Periodicals
Automation -- Periodicals
629.805 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00051098 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.automatica.2022.110656 ↗
- Languages:
- English
- ISSNs:
- 0005-1098
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1829.450000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24630.xml