Communication delays and data losses in distributed adaptive high‐gain EKF. Issue 12 (22nd June 2016)

• Record Type: Journal Article
• Authors: Rashedi, Mohammad; Liu, Jinfeng; Huang, Biao
• Is Part Of: AIChE journal. Volume 62:Issue 12(2016)
• Page Start: 4321
• Page End: 4333
• Publication Date: 2016-06-22
• Subjects: high‐gain observers -- distributed filtering -- adaptive‐gain EKF -- communication delay -- data loss; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.15351
• Languages: English
• ISSNs: 0001-1541

Abstract

Abstract : In this work, we consider distributed adaptive high‐gain extended Kalman filtering for nonlinear systems subject to data losses and delays in communications. Specifically, we consider a class of nonlinear systems that consist of several subsystems interacting with each other via their states. A local adaptive high‐gain extended Kalman filter is designed for each subsystem and the distributed estimators communicate to exchange the information. Each subsystem estimator takes the advantage of a predictor accounting for the delays and data losses simultaneously. The predictor of each subsystem is used to generate state predictions of interacting subsystems for interaction compensation. To get a reliable prediction, the predictors are designed based on a prediction‐update algorithm. The convergence of the proposed distributed state estimation is ensured under sufficient conditions handling communication delays and data losses. Finally, a chemical process example is used to evaluate the applicability and effectiveness of the proposed design. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4321–4333, 2016