TY  - JOUR
PB  - Springer
SN  - 0926-6003
A1  - Bemporad, Alberto
A1  - Filippi, Carlo
SP  - 87
N2  - For multiparametric convex nonlinear programming problems we propose a recursive algorithm for approximating, within a given suboptimality tolerance, the value function and an optimizer as functions of the parameters. The approximate solution is expressed as a piecewise affine function over a simplicial partition of a subset of the feasible parameters, and it is organized over a tree structure for efficiency of evaluation. Adaptations of the algorithm to deal with multiparametric semidefinite programming and multiparametric geometric programming are provided and exemplified. The approach is relevant for real-time implementation of several optimization-based feedback control strategies. 
Y1  - 2006///
TI  - An algorithm for approximate multiparametric convex programming
AV  - none
JF  - Computational Optimization and Applications
IS  - 1
UR  - http://link.springer.com/article/10.1007%2Fs10589-006-6447-z#
VL  - 35
ID  - eprints492
EP  - 108
ER  -