๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A pointwise projected gradient method applied to an optimal control problem

โœ Scribed by N.V. Pulova

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
356 KB
Volume
226
Category
Article
ISSN
0377-0427

No coin nor oath required. For personal study only.

โœฆ Synopsis

The aim of this work is to present a method for finding pointwise control approximations of an optimal control problem with control constraints. The method is oriented to practical applications of the gradient projection method. By applying Euler scheme to the state and costate equations we find a sequence of approximate values of the gradient. Approximate values of the control in the grid points are obtained by projecting on the set of control values. We define a sequence having an accumulation point that is at a distance Ch 1/2 (in L r 2 metric) from the optimal control. Finally, numerical examples are given.

๐Ÿ“œ SIMILAR VOLUMES

Gradient method of optimal control appli
Gradient method of optimal control applied to the operation of a dam water gate
โœ Mutsuto Kawahara; Yoshiro Shimada ๐Ÿ“‚ Article ๐Ÿ“… 1994 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 731 KB

## Abstract An extension of the authors' previous methods is presented for the optimal control of flood propagation via a dam gate, based on a combination of the finite element and gradient methods. It is assumed in previous papers that the control duration is the same as the duration of the flood.

A gradient-only line search method for t
A gradient-only line search method for the conjugate gradient method applied to constrained optimization problems with severe noise in the objective function
โœ J. A. Snyman ๐Ÿ“‚ Article ๐Ÿ“… 2004 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 100 KB

A new implementation of the conjugate gradient method is presented that economically overcomes the problem of severe numerical noise superimposed on an otherwise smooth underlying objective function of a constrained optimization problem. This is done by the use of a novel gradient-only line search t