Jian Wang Wang A Self Adaptive Real Time Optimization for Stochastic Dynamic System

A Self Adaptive Real Time Optimization for Stochastic Dynamic System

von Jian Wang

Theory of Dynamic Correlation Integration Method and Application in Petrochemical Process

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Beschreibung

This book introduces a real-time optimization (RTO) method based on the dynamic correlation integration (DCI) theory, which has the performances of modeling-free and self-adaptive model changes in real process. With this method, the implementation of RTO could be simplified in great deal comparing to traditional modeling way in many cases, and it especially benefits to the RTO of complex chemical reactions and the processes which are difficult to modeling.

This book is applicable to real-time optimization theory researchers and practical application engineers for reference.


This book introduces a real-time optimization (RTO) method based on the dynamic correlation integration (DCI) theory, which has the performances of modeling-free and self-adaptive model changes in real process. With this method, the implementation of RTO could be simplified in great deal comparing to traditional modeling way in many cases, and it especially benefits to the RTO of complex chemical reactions and the processes which are difficult to modeling.

This book is applicable to real-time optimization theory researchers and practical application engineers for reference.


The first book of theoretical research on Dynamic Correlation Integration (DCI) method for real time optimization Presents a modeling free, self adaptive unique real time optimization method Introduce the application examples of DCI optimizer

Autor*in

Jian Wang

Themen in »A Self Adaptive Real Time Optimization for Stochastic Dynamic System«

Real Time Optimization Self Adaptive Modling Free Random Process Refinery Fluid Catalytic Cracking (FCC)

Stimmen zu »A Self Adaptive Real Time Optimization for Stochastic Dynamic System«

Details

ISBN: 9789819606313
Verlag: Springer Singapore
Erscheinung: 22.06.2025

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