[{"type":"paper-conference","title":"Distributed and Decentralized Kalman Filtering for Cascaded Fractional Order Systems","issued":{"date-parts":[["2017"]]},"page":"5223-5230","container-title":"Proceedings of the 2017 American Control Conference (ACC), Seattle, Washington, USA, 24th - 26th May 2017","DOI":"10.23919\/ACC.2017.7963766","author":[{"family":"Kupper","given":"Martin"},{"family":"Gil","given":"Inigo Sesar"},{"family":"Hohmann","given":"S\u00f6ren"}],"publisher":"IEEE","publisher-place":"Piscataway (NJ)","ISBN":"978-1-5090-5992-8","abstract":"This paper presents a distributed Kalman filter algorithm for cascaded systems of fractional order. Certain conditions are introduced under which a division of a fractional system into cascaded subsystems is possible. A functional distribution of a large scale system and of the state estimation algorithm leads to smaller and scalable nodes with reduced memory and computational effort. Since each subsystem performs its calculations locally, a central processing node is not needed. All data which are required by subsequent nodes are communicated to them unidirectionally. Also a comparison between the Fractional Kalman Filter (FKF) and the Cascaded Fractional Kalman Filter (CFKF) is given by an example.","kit-publication-id":"1000071710"}]