Most of the discretization approaches for uncertain linear systems make use of the series representation of the matrix exponential function and truncate the summation after a certain order. This usually leads to discrete-time uncertain polytopic models described by polynomial matrices with multiple indexes, which usually means that the higher the order used in the approximation, the higher the number of linear matrix inequalities (LMI) needed. This work, instead, proposes an approach based on a grid of the possible values for the matrix exponential function and an application of the tensor product model transformation technique to find a suitable polytopic model. Numerical examples are presented to illustrate the advantages and the applicab...
This investigation is concerned with robust analysis and control of uncertain nonlinear systems with...
The robust stability of uncertain linear systems in polytopic domains is investigated in this paper....
This paper presents a method for using set-based approxi-mations to the Peano-Baker series to comput...
Abstract — The Tensor Product (TP) model transformation is a recently proposed technique for transfo...
In this paper, a convergent numerical procedure to compute H-2 and H-infinity norms of uncertain tim...
This paper addresses the problem of constant sampling discretization of uncertain time-invariant con...
International audienceContinuous-time linear systems with uncertain parameters are widely used for m...
Computational uncertainty quantication in a probabilistic setting is a special case of a parametric ...
One of the methods recently utilized in stability robustness analysis uses various matrix compositio...
We survey the problem of deciding the stability or stabilizability of uncertain linear systems whose...
The paper investigates the possibility of the Tensor Product (TP) type polytopic modelling of the qu...
Part 2: UQ TheoryInternational audienceComputational uncertainty quantification in a probabilistic s...
This paper aims at handling high dimensional uncertainty propagation problems by proposing a tensor ...
International audienceThis paper determines an explicit upper bound to the norm of any given degree ...
This paper introduces the novel concept of Affine Tensor Product (TP) Model and the corresponding mo...
This investigation is concerned with robust analysis and control of uncertain nonlinear systems with...
The robust stability of uncertain linear systems in polytopic domains is investigated in this paper....
This paper presents a method for using set-based approxi-mations to the Peano-Baker series to comput...
Abstract — The Tensor Product (TP) model transformation is a recently proposed technique for transfo...
In this paper, a convergent numerical procedure to compute H-2 and H-infinity norms of uncertain tim...
This paper addresses the problem of constant sampling discretization of uncertain time-invariant con...
International audienceContinuous-time linear systems with uncertain parameters are widely used for m...
Computational uncertainty quantication in a probabilistic setting is a special case of a parametric ...
One of the methods recently utilized in stability robustness analysis uses various matrix compositio...
We survey the problem of deciding the stability or stabilizability of uncertain linear systems whose...
The paper investigates the possibility of the Tensor Product (TP) type polytopic modelling of the qu...
Part 2: UQ TheoryInternational audienceComputational uncertainty quantification in a probabilistic s...
This paper aims at handling high dimensional uncertainty propagation problems by proposing a tensor ...
International audienceThis paper determines an explicit upper bound to the norm of any given degree ...
This paper introduces the novel concept of Affine Tensor Product (TP) Model and the corresponding mo...
This investigation is concerned with robust analysis and control of uncertain nonlinear systems with...
The robust stability of uncertain linear systems in polytopic domains is investigated in this paper....
This paper presents a method for using set-based approxi-mations to the Peano-Baker series to comput...