Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control

Ch. Venkateswarlu, Rama Rao Karri

• Publisher: Elsevier
• Year: 2022
• Print ISBN: 9780323858786
• eBook ISBN: 9780323900683
• Topic: Technology & Engineering
• Subtopic: Business Intelligence
• Index: Technology & Engineering

Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field.Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines.- Describes various classical and advanced versions of mechanistic model based state estimation algorithms- Describes various data-driven model based state estimation techniques- Highlights a number of real applications of mechanistic model based and data-driven model based state estimators/soft sensors- Beneficial to those associated with process monitoring, fault diagnosis, online optimization, control and related areas

Table of contents

• Cover
• Title page
• Table of Contents
• Copyright
• Contents
• About the authors
• Preface
• List of Illustrations
• List of Tables
• Chapter 1 : Optimal state estimation and its importance in process systems engineering
• Chapter 2 : Introduction to stochastic processes and state estimation filtering
• Chapter 3 : Linear filtering and observation techniques
• Chapter 4 : Mechanistic model-based nonlinear filtering and observation techniques for optimal state/parameter estimation
• Chapter 5 : Data-driven modeling techniques for state estimation
• Chapter 6 : Optimal sensor configuration methods for state estimation
• Chapter 7 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation in multicomponent batch distillation
• Chapter 8 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation in multicomponent reactive batch distillation with optimal sensor configuration
• Chapter 9 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation in complex nonlinear dynamical systems
• Chapter 10 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation of a kraft pulping digester
• Chapter 11 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation of a continuous reactive distillation column with optimal sensor configuration
• Chapter 12 : Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation of a catalytic tubular reactor with optimal sensor configuration
• Chapter 13 : Applications of data-driven model-based methods for process state estimation
• Chapter 14 : Optimal state and parameter estimation for fault detection and diagnosis in continuous stirred tank reactor
• Chapter 15 : Optimal state and parameter estimation for fault detection and diagnosis of a nonlinear batch beer fermentation process
• Chapter 16 : Optimal state and parameter estimation for fault detection and diagnosis of a high-dimensional fluid catalytic cracking unit
• Chapter 17 : Optimal state estimator-based inferential control of continuous reactive distillation column
• Chapter 18 : Optimal state estimation for nonlinear control of complex dynamic systems
• Chapter 19 : Optimal state estimator based control of an exothermic batch chemical reactor
• Chapter 20 : Optimal state and parameter estimation for online optimization of an uncertain biochemical reactor
• Chapter 21 : Overview, opportunities, challenges, and future directions of state estimation
• Index
• A