Paper Info
Title
Deadbeat Simultaneous Parameter-State Estimation For Linear Continuous-Time Systems: A Kernel-Based Approach
Abstract
The simultaneous estimation of parameters and states in continuous-time linear MISO systems is considered in this paper. The estimates of system's parameters and states are provided simultaneously by a single estimator, where Volterra operators are suitably applied to the I/O measurements. This makes the estimator independent on the initial conditions thanks to the design of suitably shaped kernel functions equipped with non-asymptotic properties. As a result, in the noise-free scenario, instantaneous convergence can be obtained. No high-gain injection nor periodic resetting is necessary. Numerical examples are reported showing the effectiveness of the proposed estimator.
Year
DOI
Venue
2018
10.23919/ECC.2018.8550508
2018 EUROPEAN CONTROL CONFERENCE (ECC)
Field
DocType
Citations 
Convergence (routing),Kernel (linear algebra),Applied mathematics,Operator (computer programming),Periodic graph (geometry),Mathematics,Kernel (statistics),Estimator
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Peng Li102.03
Francesca Boem28312.10
Gilberto Pin313617.21
T Parisini4935113.17