Add to ORKGAbstract-This paper deals with the problem of model (in)validation of discrete-time, causal, LTI stable models subject to Slowly Linear Time Varying structured uncertainly, using freqnency-domain data corrupted by additive noise. It is nell known that in the case of structured LTI uncertainty the problem is NP hard in the number of uncertainty blocks. The main contribution of this paper shows that, on the other hand, if one considers arbitrarily slowly time varying uncertainty and noise in U;, then tractable, convex necessary and sufficient conditions for (in)validation can be obtained
This thesis is concerned with the analysis of dynamical systems in the presence of model uncertainty...
This paper introduces methods of deriving and computing maximal robust positively invariant sets for...
Abstract: The observability of discrete linear time-varying (LTV) systems with norm-bounded paramete...
In this raper we study a model validation problem pertaining to linear fractional uncertainty models...
In this paper the authors study a model validation problem pertaining to linear fractional uncertain...
In this paper, a less conservative condition for the robust stability of uncertain discrete-time lin...
New methods for model validation of continuous-time nonlinear systems with uncertain parameters are ...
Given measured data generated by a discrete-time linear system we propose a model consisting of a li...
The work presented in this dissertation deals with the theoretical analysis of the frequency domain ...
[[abstract]]Structured singular value (SSV or µ ) theory is known to be an effective tool for assess...
In this paper, we consider the identification of linear systems, a priori known to be stable, from ...
In this chapter, we consider the identification of single-input single-output linear-parameter-varyi...
In this chapter we present a control-oriented identification and (in)validation framework for a clas...
In this paper, we consider the identification of linear systems, a priori known to be stable, from i...
Given measurement data, a nominal model and a linear fractional transformation uncertainty structure...
This thesis is concerned with the analysis of dynamical systems in the presence of model uncertainty...
This paper introduces methods of deriving and computing maximal robust positively invariant sets for...
Abstract: The observability of discrete linear time-varying (LTV) systems with norm-bounded paramete...
In this raper we study a model validation problem pertaining to linear fractional uncertainty models...
In this paper the authors study a model validation problem pertaining to linear fractional uncertain...
In this paper, a less conservative condition for the robust stability of uncertain discrete-time lin...
New methods for model validation of continuous-time nonlinear systems with uncertain parameters are ...
Given measured data generated by a discrete-time linear system we propose a model consisting of a li...
The work presented in this dissertation deals with the theoretical analysis of the frequency domain ...
[[abstract]]Structured singular value (SSV or µ ) theory is known to be an effective tool for assess...
In this paper, we consider the identification of linear systems, a priori known to be stable, from ...
In this chapter, we consider the identification of single-input single-output linear-parameter-varyi...
In this chapter we present a control-oriented identification and (in)validation framework for a clas...
In this paper, we consider the identification of linear systems, a priori known to be stable, from i...
Given measurement data, a nominal model and a linear fractional transformation uncertainty structure...
This thesis is concerned with the analysis of dynamical systems in the presence of model uncertainty...
This paper introduces methods of deriving and computing maximal robust positively invariant sets for...
Abstract: The observability of discrete linear time-varying (LTV) systems with norm-bounded paramete...