Title
Empirical differential Gramians for nonlinear model reduction
Abstract
In this paper, we present an empirical balanced truncation method for nonlinear systems whose input vector fields are constants. First, we define differential reachability and observability Gramians. They are matrix valued functions of the state trajectory (i.e. the initial state and input trajectory), and it is difficult to find them as functions of the initial state and input. The main result of this paper is to show that for a fixed state trajectory, it is possible to compute the values of these Gramians by using impulse and initial state responses of the variational system. Therefore, balanced truncation is doable along the fixed state trajectory without solving nonlinear partial differential equations, differently from conventional nonlinear balancing methods. We further develop an approximation method, which only requires trajectories of the original nonlinear systems.
Year
DOI
Venue
2019
10.1016/j.automatica.2021.109534
Automatica
Keywords
DocType
Volume
Model reduction,Nonlinear systems,Balanced truncation,Proper orthogonal decomposition
Journal
127
Issue
ISSN
Citations 
1
0005-1098
1
PageRank 
References 
Authors
0.35
10
2
Name
Order
Citations
PageRank
Yu Kawano15116.84
Jacquelien M. A. Scherpen249195.93