In this paper, a stability preserving model reduction algorithm for single-input single-output linear time invariant systems is presented. It performs a data fitting in the frequency domain using semidefinite programming methods. Computing the frequency response of a model can be done efficiently even for large scale models making this approach applicable to those. The relaxation used to obtain a semidefinite program is similar to one used in Hankel model reduction. Therefore accuracy of approximation is also similar to Hankel model reduction one. The approach can be easily extended to frequency-weighted and parameter dependent model reduction problems
The author presented a method for model order reduction of large-scale time-invariant systems in tim...
The author presented a method for model order reduction of large-scale time-invariant system...
A new model reduction method, based on frequency fitting, is proposed for single-input discrete-time...
This paper is dedicated to model order reduction of linear time-invariant systems. The main contribu...
In this thesis model reduction methods for linear time invariant systems are investigated. The reduc...
A parametrized model in addition to the control and state-space variables depends on time-independen...
In this paper a modification of a recently proposed model simplification method for linear time inva...
A newly proposed method of frequency-weighted model reduction for single-input–single-output (SISO) ...
A parametrized model in addition to the control and state-space variables depends on time-independen...
A parametrized model in addition to the control and state-space variables depends on time-independen...
A new stability preserving model reduction algorithm for discrete linear SISO-systems based on their...
Abstract — In this paper, a frequency-weighted extension of a recently proposed model reduction meth...
Abstract — In this paper, a frequency-weighted extension of a recently proposed model reduction meth...
Model reduction is a process of approximating higher order original models by comparatively lower or...
The author presented a method for model order reduction of large-scale time-invariant system...
The author presented a method for model order reduction of large-scale time-invariant systems in tim...
The author presented a method for model order reduction of large-scale time-invariant system...
A new model reduction method, based on frequency fitting, is proposed for single-input discrete-time...
This paper is dedicated to model order reduction of linear time-invariant systems. The main contribu...
In this thesis model reduction methods for linear time invariant systems are investigated. The reduc...
A parametrized model in addition to the control and state-space variables depends on time-independen...
In this paper a modification of a recently proposed model simplification method for linear time inva...
A newly proposed method of frequency-weighted model reduction for single-input–single-output (SISO) ...
A parametrized model in addition to the control and state-space variables depends on time-independen...
A parametrized model in addition to the control and state-space variables depends on time-independen...
A new stability preserving model reduction algorithm for discrete linear SISO-systems based on their...
Abstract — In this paper, a frequency-weighted extension of a recently proposed model reduction meth...
Abstract — In this paper, a frequency-weighted extension of a recently proposed model reduction meth...
Model reduction is a process of approximating higher order original models by comparatively lower or...
The author presented a method for model order reduction of large-scale time-invariant system...
The author presented a method for model order reduction of large-scale time-invariant systems in tim...
The author presented a method for model order reduction of large-scale time-invariant system...
A new model reduction method, based on frequency fitting, is proposed for single-input discrete-time...