Distributed Adaptive High-Gain Extended Kalman Filtering for Nonlinear systems. Issue 8 (2015)

• Record Type: Journal Article
• Authors: Rashedi, Mohammad; Liu, Jinfeng; Huang, Biao
• Is Part Of: IFAC-PapersOnLine. Volume 48:Issue 8(2015)
• Page Start: 158
• Page End: 163
• Publication Date: 2015
• Subjects: Distributed state estimation -- Extended Kalman filter -- Nonlinear systems -- High gain observer; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2015.08.174
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In this work, we propose a distributed adaptive high-gain extended Kalman filtering approach for nonlinear systems. Specifically, we consider a class of nonlinear systems that are composed of several subsystems interacting with each other via their states. In the proposed approach, an adaptive high-gain extended Kalman filter is designed for each subsystem. The distributed Kalman filters communicate with each other to exchange subsystem state estimates. First, an implementation strategy which specifies how the distributed filters should communicate is designed. Second, the detailed design of the subsystem filter is described. Subsequently, the stability of the proposed distributed state estimation is analyzed. Finally, the effectiveness and applicability of the proposed design are illustrated via the application to a chemical process example.