In this paper the authors study a model validation problem pertaining to linear fractional uncertainty models. They extend the previous validation approaches, based upon either time or frequency measurements, to one using simultaneously time- and frequency-domain data. They show that this problem can be reduced to two independent convex feasibility tests, each of which corresponds to the time- or frequency-domain data alone, and each can be verified numerically using available algorithms and software programs. The merit of such a mixed time- and frequency-domain approach, therefore, lies in that not only can it accommodate the two distinctively different types of measurement data simultaneously, but also from a computational standpoint it w...
Abstract The majority of literature on robust control assumes that a design model is available and t...
This paper investigates the generalized uncertainty principles of fractional Fourier transform (FRFT...
Model validation is a means of assessing model quality with respect to experimental data. In a robus...
In this raper we study a model validation problem pertaining to linear fractional uncertainty models...
The model validation problem using time-domain experimental data is studied for multirate linear fra...
Abstract-This paper deals with the problem of model (in)validation of discrete-time, causal, LTI sta...
Model validation provides a useful means of assessing the ability of a model to account for a specif...
Uncertainty validation using frequency response data has been studied by several authors. If the unc...
A new methodology in which linear fractional transformation uncertainty bounds are directly construc...
Given measurement data, a nominal model and a linear fractional transformation uncertainty structure...
This report attempts to document the broad scope of issues that must be satisfactorily resolved befo...
The work presented in this dissertation deals with the theoretical analysis of the frequency domain ...
Given a nominal model, an integrated uncertainty model identification and mu-synthesis algorithm is ...
Abstract—The fractional Fourier transform (FrFT) can be thought of as a generalization of the Fourie...
The fractional Fourier transform (FrFT) can be thought of as a generalization of the Fourier transfo...
Abstract The majority of literature on robust control assumes that a design model is available and t...
This paper investigates the generalized uncertainty principles of fractional Fourier transform (FRFT...
Model validation is a means of assessing model quality with respect to experimental data. In a robus...
In this raper we study a model validation problem pertaining to linear fractional uncertainty models...
The model validation problem using time-domain experimental data is studied for multirate linear fra...
Abstract-This paper deals with the problem of model (in)validation of discrete-time, causal, LTI sta...
Model validation provides a useful means of assessing the ability of a model to account for a specif...
Uncertainty validation using frequency response data has been studied by several authors. If the unc...
A new methodology in which linear fractional transformation uncertainty bounds are directly construc...
Given measurement data, a nominal model and a linear fractional transformation uncertainty structure...
This report attempts to document the broad scope of issues that must be satisfactorily resolved befo...
The work presented in this dissertation deals with the theoretical analysis of the frequency domain ...
Given a nominal model, an integrated uncertainty model identification and mu-synthesis algorithm is ...
Abstract—The fractional Fourier transform (FrFT) can be thought of as a generalization of the Fourie...
The fractional Fourier transform (FrFT) can be thought of as a generalization of the Fourier transfo...
Abstract The majority of literature on robust control assumes that a design model is available and t...
This paper investigates the generalized uncertainty principles of fractional Fourier transform (FRFT...
Model validation is a means of assessing model quality with respect to experimental data. In a robus...