We propose a Reduced Basis method for the solution of parametrized optimal control problems with control constraints for which we extend the method proposed in Dedè, L. (SIAM J. Sci. Comput. 32:997, 2010) for the unconstrained problem. The case of a linear-quadratic optimal control problem is considered with the primal equation represented by a linear parabolic partial differential equation. The standard offline-online decomposition of the Reduced Basis method is employed with the Finite Element approximation as the "truth" one for the offline step. An error estimate is derived and an heuristic indicator is proposed to evaluate the Reduced Basis error on the optimal control problem at the online step; also, the indicator is used at the offl...
In this thesis a reliable and (numerical) efficient a-posteriori error estimation for reduced order ...
Abstract. In this work, we study priori error estimates for the numerical ap-proximation of an optim...
AbstractThis paper deals with optimal algorithms for the approximate solution of a problem of optima...
We propose a Reduced Basis method for the solution of parametrized optimal control problems with con...
We propose the reduced basis method for the solution of parametrized optimal control problems descri...
In this paper, we employ the reduced basis method as a surrogate model for the solution of...
In this thesis, we address new reduced basis approaches for parametrized variational inequalities an...
We propose a suitable model reduction paradigm---the certified reduced basis method (RB)---for the r...
We present a new reduced basis approach for the efficient and reliable solution of parametrized PDE-...
In this thesis we present new methods for the analysis, simulation, and control of parameter-depende...
We present a certified reduced basis (RB) framework for the efficient solution of PDE-constrained pa...
In this work we provide efficient numerical methods for the numerical solution of Partial Differenti...
The main focus of this paper is on an a-posteriori analysis for different model-order strategies app...
Abstract — The reduced basis (RB) method is proposed for the approximation of multi-parametrized equ...
In this paper, we derive a posteriori error estimates for the finite element approximation of quadra...
In this thesis a reliable and (numerical) efficient a-posteriori error estimation for reduced order ...
Abstract. In this work, we study priori error estimates for the numerical ap-proximation of an optim...
AbstractThis paper deals with optimal algorithms for the approximate solution of a problem of optima...
We propose a Reduced Basis method for the solution of parametrized optimal control problems with con...
We propose the reduced basis method for the solution of parametrized optimal control problems descri...
In this paper, we employ the reduced basis method as a surrogate model for the solution of...
In this thesis, we address new reduced basis approaches for parametrized variational inequalities an...
We propose a suitable model reduction paradigm---the certified reduced basis method (RB)---for the r...
We present a new reduced basis approach for the efficient and reliable solution of parametrized PDE-...
In this thesis we present new methods for the analysis, simulation, and control of parameter-depende...
We present a certified reduced basis (RB) framework for the efficient solution of PDE-constrained pa...
In this work we provide efficient numerical methods for the numerical solution of Partial Differenti...
The main focus of this paper is on an a-posteriori analysis for different model-order strategies app...
Abstract — The reduced basis (RB) method is proposed for the approximation of multi-parametrized equ...
In this paper, we derive a posteriori error estimates for the finite element approximation of quadra...
In this thesis a reliable and (numerical) efficient a-posteriori error estimation for reduced order ...
Abstract. In this work, we study priori error estimates for the numerical ap-proximation of an optim...
AbstractThis paper deals with optimal algorithms for the approximate solution of a problem of optima...