Periodic Event-Triggered Estimation for Networked Control Systems

This paper considers the problem of remote state estimation in a linear discrete invariant system, where a smart sensor is utilized to measure the system state and generate a local estimate. The communication depends on an event scheduler in the smart sensor. When the channel between the remote esti...

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Main Authors: Shitong Cui, Le Liu, Wei Xing, Xudong Zhao
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/10/18/2215
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spelling doaj-164049610fa743c9ac52d996be69905b2021-09-26T00:03:08ZengMDPI AGElectronics2079-92922021-09-01102215221510.3390/electronics10182215Periodic Event-Triggered Estimation for Networked Control SystemsShitong Cui0Le Liu1Wei Xing2Xudong Zhao3The Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education, Dalian University of Technology, Dalian 116000, ChinaThe Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education, Dalian University of Technology, Dalian 116000, ChinaThe Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education, Dalian University of Technology, Dalian 116000, ChinaThe Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education, Dalian University of Technology, Dalian 116000, ChinaThis paper considers the problem of remote state estimation in a linear discrete invariant system, where a smart sensor is utilized to measure the system state and generate a local estimate. The communication depends on an event scheduler in the smart sensor. When the channel between the remote estimator and the smart sensor is activated, the remote estimator simply adopts the estimate transmitted by the smart sensor. Otherwise, it calculates an estimate based on the available information. The closed-form of the minimum mean-square error (MMSE) estimator is introduced, and we use Gaussian preserving event-based sensor scheduling to obtain an ideal compromise between the communication cost and estimation quality. Furthermore, we calculate a variation range of communication probability, which helps to design the policy of event-triggered estimation. Finally, the simulation results are given to illustrate the effectiveness of the proposed event-triggered estimator.https://www.mdpi.com/2079-9292/10/18/2215networked control systemsevent-triggeredestimationKalman filtering
collection DOAJ
language English
format Article
sources DOAJ
author Shitong Cui
Le Liu
Wei Xing
Xudong Zhao
spellingShingle Shitong Cui
Le Liu
Wei Xing
Xudong Zhao
Periodic Event-Triggered Estimation for Networked Control Systems
Electronics
networked control systems
event-triggered
estimation
Kalman filtering
author_facet Shitong Cui
Le Liu
Wei Xing
Xudong Zhao
author_sort Shitong Cui
title Periodic Event-Triggered Estimation for Networked Control Systems
title_short Periodic Event-Triggered Estimation for Networked Control Systems
title_full Periodic Event-Triggered Estimation for Networked Control Systems
title_fullStr Periodic Event-Triggered Estimation for Networked Control Systems
title_full_unstemmed Periodic Event-Triggered Estimation for Networked Control Systems
title_sort periodic event-triggered estimation for networked control systems
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2021-09-01
description This paper considers the problem of remote state estimation in a linear discrete invariant system, where a smart sensor is utilized to measure the system state and generate a local estimate. The communication depends on an event scheduler in the smart sensor. When the channel between the remote estimator and the smart sensor is activated, the remote estimator simply adopts the estimate transmitted by the smart sensor. Otherwise, it calculates an estimate based on the available information. The closed-form of the minimum mean-square error (MMSE) estimator is introduced, and we use Gaussian preserving event-based sensor scheduling to obtain an ideal compromise between the communication cost and estimation quality. Furthermore, we calculate a variation range of communication probability, which helps to design the policy of event-triggered estimation. Finally, the simulation results are given to illustrate the effectiveness of the proposed event-triggered estimator.
topic networked control systems
event-triggered
estimation
Kalman filtering
url https://www.mdpi.com/2079-9292/10/18/2215
work_keys_str_mv AT shitongcui periodiceventtriggeredestimationfornetworkedcontrolsystems
AT leliu periodiceventtriggeredestimationfornetworkedcontrolsystems
AT weixing periodiceventtriggeredestimationfornetworkedcontrolsystems
AT xudongzhao periodiceventtriggeredestimationfornetworkedcontrolsystems
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