A new approach for computing upper error bounds for reduced-order models of linear time-varying systems is presented. It is based on a transformation technique of the Hankel singular values using positive-real, odd incremented functions. By applying such time-varying functions, the singular values to be removed can be forced to become equal and constant, so that they can be reduced. Two variations of this method are proposed: one for finite-time horizons and the other for infinite-time problems including periodic systems
We present a simple bound on the finite horizon L2 [0, TI-induced norm of a linear time-invariant (L...
Linear time-invariant models are widely used in the control community. They often serve as approxima...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
A new approach for computing upper error bounds for reduced-order models of linear time-varying syst...
Abstract—Error-bounds are developed for balanced truncation of linear time-varying systems, leading ...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
The thesis treats model reduction for linear time-varying systems. Time-varying models appear in man...
A new mixed method for relative error model reduction of linear time invariant (LTI) systems is prop...
In this article, a new method for model reduction of linear dynamical systems is presented. The prop...
In this paper, we address the H ∞ model reduction problem for linear time-invariant discrete-time sy...
Abstract—In this paper, balanced truncation of linear time-varying systems is studied in discrete an...
ABSTRACT In recent years, a great effort has been taken focused on the development of reduced order ...
The analysis of a posteriori error estimates used in reduced basis methods leads to a model reductio...
We present a simple bound on the finite horizon L2 [0, TI-induced norm of a linear time-invariant (L...
Linear time-invariant models are widely used in the control community. They often serve as approxima...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...
A new approach for computing upper error bounds for reduced-order models of linear time-varying syst...
Abstract—Error-bounds are developed for balanced truncation of linear time-varying systems, leading ...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
We propose a posteriori error bounds for reduced-order models of non-parametrized linear time invari...
The thesis treats model reduction for linear time-varying systems. Time-varying models appear in man...
A new mixed method for relative error model reduction of linear time invariant (LTI) systems is prop...
In this article, a new method for model reduction of linear dynamical systems is presented. The prop...
In this paper, we address the H ∞ model reduction problem for linear time-invariant discrete-time sy...
Abstract—In this paper, balanced truncation of linear time-varying systems is studied in discrete an...
ABSTRACT In recent years, a great effort has been taken focused on the development of reduced order ...
The analysis of a posteriori error estimates used in reduced basis methods leads to a model reductio...
We present a simple bound on the finite horizon L2 [0, TI-induced norm of a linear time-invariant (L...
Linear time-invariant models are widely used in the control community. They often serve as approxima...
In this note we present a new updating technique to estimate a low rank approximation of the Hankel ...