Paper Info
Title
Inverse Problems for Matrix Exponential in System Identification: System Aliasing.
Abstract
This note addresses identification of the $A$-matrix in continuous time linear dynamical systems on state-space form. If this matrix is partially known or known to have a sparse structure, such knowledge can be used to simplify the identification. We begin by introducing some general conditions for solvability of the inverse problems for matrix exponential. Next, we introduce as an issue in the identification of slow sampled systems. Such aliasing give rise to non-unique matrix logarithms. As we show, by imposing additional conditions on and prior knowledge about the $A$-matrix, the issue of system aliasing can, at least partially, be overcome. Under conditions on the sparsity and the norm of the $A$-matrix, it is identifiable up to a finite equivalence class.
Year
Venue
Field
2016
arXiv: Systems and Control
Linear dynamical system,Mathematical optimization,Matrix (mathematics),Control theory,Aliasing,Inverse problem,Logarithm,State-transition matrix,System identification,Matrix exponential,Mathematics
DocType
Volume
Citations 
Journal
abs/1605.06973
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Zuogong Yue101.35
Johan Thunberg213819.15
Jorge M. Gonçalves35119.23