Iterative Algorithms For Multilayer Optimizing Control
Download Iterative Algorithms For Multilayer Optimizing Control PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Iterative Algorithms For Multilayer Optimizing Control book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Iterative Algorithms For Multilayer Optimizing Control
The book presents basic structures, concepts and algorithms in the area of multilayer optimizing control of industrial systems, as well as the results of the research that was carried out by the authors over the last two decades. The methodologies and control algorithms are thoroughly illustrated by numerous simulation examples. Also, the applications to several case study examples are presented. These include ethylene distillation column, vaporizer pilot scale plant, styrene distillation line consisting of three columns and industrial furnace pilot scale plant. A temporal decomposition is applied to the Integrated Wastewater System case study to derive multilayer dynamic optimizing controller with repetitive robust model predictive control mechanism distributed over the layers operating in different time scales.Sample Chapter(s)
Real-Time Optimization
This book is a printed edition of the Special Issue "Real-Time Optimization" that was published in Processes
Advanced Control of Industrial Processes
Author: Piotr Tatjewski
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-02-23
This book presents the concepts and algorithms of advanced industrial process control and on-line optimization within the framework of a multilayer structure. It describes the interaction of three separate layers of process control: direct control, set-point control, and economic optimization. The book features illustrations of the methodologies and algorithms by worked examples and by results of simulations based on industrial process models.