Non-Fiction Books:

Optimal Control of PDEs under Uncertainty

An Introduction with Application to Optimal Shape Design of Structures

Customer rating

Click to share your rating 0 ratings (0.0/5.0 average) Thanks for your vote!

Share this product

Optimal Control of PDEs under Uncertainty by Jesus Martinez-Frutos
Save $56.00
$95.99 was $151.99
or 4 payments of $24.00 with Learn more
Releases

Pre-order to reserve stock from our first shipment. Your credit card will not be charged until your order is ready to ship.

Available for pre-order now
Pre-order Price Guarantee

If you pre-order an item and the price drops before the release date, you’ll pay the lowest price. This happens automatically when you pre-order and pay by credit card.

If paying by PayPal or internet banking, and the price drops after you have paid, you can ask for the difference to be refunded. Find out more

If Mighty Ape's price changes before release, you'll pay the lowest price.

Availability

This product will be released on

Delivering to:

It should arrive:

  • 25-29 October using standard courier delivery

Description

This book provides a direct and comprehensive introduction to theoretical and numerical concepts in the emerging field of optimal control of partial differential equations (PDEs) under uncertainty. The main objective of the book is to offer graduate students and researchers a smooth transition from optimal control of deterministic PDEs to optimal control of random PDEs. Coverage includes uncertainty modelling in control problems, variational formulation of PDEs with random inputs, robust and risk-averse formulations of optimal control problems, existence theory and numerical resolution methods. The exposition focusses on the entire path, starting from uncertainty modelling and ending in the practical implementation of numerical schemes for the numerical approximation of the considered problems. To this end, a selected number of illustrative examples are analysed in detail throughout the book. Computer codes, written in MatLab, are provided for all these examples. This book is adressed to graduate students and researches in Engineering, Physics and Mathematics who are interested in optimal control and optimal design for random partial differential equations.

Author Biography

Jesus Martinez-Frutos obtained his PhD from the Technical University of Cartagena, Spain, in 2014 and is currently Assistant Professor in the Department of Structures and Construction and a member of the Computational Mechanics and Scientific Computing group at the Technical University of Cartagena, Spain. His research interests are in the field of robust optimal control, structural optimization under uncertainty, efficient methods for high-dimensional uncertainty propagation and high-performance computing using GPUs, with special focus on industrial applications. Francisco Periago Esparza completed his PhD at the University of Valencia, Spain, in 1999. He is currently Associate Professor in the Department of Applied Mathematics and Statistics and a member of the Computational Mechanics and Scientific Computing group at the Technical University of Cartagena, Spain. His main research interests include optimal control, optimal design and controllability, both at the theoretical level and for applications to engineering problems. During recent years his research has focused on optimal control for random PDEs.
Release date Australia
October 20th, 2018
Country of Publication
Switzerland
Edition
1st ed. 2018
Illustrations
37 Illustrations, color; 8 Illustrations, black and white; XIX, 125 p. 45 illus., 37 illus. in color.
Imprint
Springer International Publishing AG
Pages
125
ISBN-13
9783319982090
Product ID
28247051

Customer previews

Nobody has previewed this product yet. You could be the first!

Write a Preview

Help & options

  • If you think we've made a mistake or omitted details, please send us your feedback. Send Feedback
  • If you have a question or problem with this product, visit our Help section. Get Help
  • Seen a lower price for this product elsewhere? We'll do our best to beat it. Request a better price
Filed under...