Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertainties are column-wise and reside in general convex sets, we show that the intersection of the set of possible solutions and any orthant is convex.We derive a convex representation of this intersection. Secondly, to obtain centered solutions for systems of uncertain linear equations, we compute the maximum size inscribed convex body (MCB) of the set of all possible solutions. The obtained MCB is an inner approximation of the solution set, and its center is a potential solution to the system. We compare our method both theoretically and numerically with an existing method that minimizes the worst-case violation. Applications to the input-output ...
The analysis and control of nonlinear systems often require information about the location of their ...
AbstractLeast squares solution of linear inequalities appears in many disciplines such as linear sep...
We derive computationally tractable formulations of the robust counterparts of convex quadratic and ...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids th...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids t...
This paper addresses the estimation of the set of admissible solutions of uncertain polynomial syste...
We treat in this paper Linear Programming (LP) problems with uncertain data. The focus is on uncerta...
We treat in this paper linear programming (LP) problems with uncertain data. The focus is on uncerta...
Uncertain constraints with convex uncertainty are in general difficult to tackle for "normal" RO. Ho...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
This paper proposes a method for solving robust optimal control problems with modulated uncertainty ...
We present an exact formula for the radius of robust feasibility of uncertain linear programs with a...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
The analysis and control of nonlinear systems often require information about the location of their ...
AbstractLeast squares solution of linear inequalities appears in many disciplines such as linear sep...
We derive computationally tractable formulations of the robust counterparts of convex quadratic and ...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids th...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids t...
This paper addresses the estimation of the set of admissible solutions of uncertain polynomial syste...
We treat in this paper Linear Programming (LP) problems with uncertain data. The focus is on uncerta...
We treat in this paper linear programming (LP) problems with uncertain data. The focus is on uncerta...
Uncertain constraints with convex uncertainty are in general difficult to tackle for "normal" RO. Ho...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
This paper proposes a method for solving robust optimal control problems with modulated uncertainty ...
We present an exact formula for the radius of robust feasibility of uncertain linear programs with a...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
The analysis and control of nonlinear systems often require information about the location of their ...
AbstractLeast squares solution of linear inequalities appears in many disciplines such as linear sep...
We derive computationally tractable formulations of the robust counterparts of convex quadratic and ...