Title
Event-based state estimation with variance-based triggering
Abstract
An event-based state estimation scenario is considered where multiple distributed sensors sporadically transmit observations of a linear process to a time-varying Kalman filter via a common bus. The triggering decision is based on the estimation variance: each sensor runs a copy of the Kalman filter and transmits its measurement only if the associated measurement prediction variance exceeds a tolerable threshold. The resulting variance iteration is a new type of Riccati equation, with switching between modes that correspond to the available measurements and depend on the variance at the previous step. Convergence of the switching Riccati equation to periodic solutions is observed in simulations, and proven for the case of an unstable scalar system (under certain assumptions). The proposed method can be implemented in two different ways: as an event-based scheme where transmit decisions are made online, or as a time-based periodic transmit schedule if a periodic solution to the switching Riccati equation is found.
Year
DOI
Venue
2014
10.1109/CDC.2012.6426352
IEEE Trans. Automat. Contr.
Keywords
DocType
Volume
distributed estimation,kalman filters,periodic solution,time-varying systems,state estimation,measurement prediction variance,unstable scalar system,riccati equations,time-varying kalman filter,switching riccati equation convergence,triggering decision,switching function,event-based state estimation,riccati equation,variance iteration,sensor scheduling,transmit decisions,remote estimator,convergence of numerical methods,asymptotic convergence,switching riccati equation,periodic control,time-based periodic transmit schedule,recursive estimation,scalar linear process,networked control systems,distributed sensors,recursive equation,variance-based triggering,iterative methods,associated measurement prediction variance,estimation variance
Journal
59
Issue
ISSN
ISBN
12
0743-1546 E-ISBN : 978-1-4673-2064-1
978-1-4673-2064-1
Citations 
PageRank 
References 
61
1.86
13
Authors
2
Name
Order
Citations
PageRank
Sebastian Trimpe119419.26
Raffaello D'andrea21592162.96