Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control
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Form:Einzelkauf Download
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Sprache:Englisch
185,00 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
31.01.2022
Verlag
Elsevier Science & Techn.Seitenzahl
366 (Printausgabe)
Dateigröße
53125 KB
Sprache
Englisch
EAN
9780323900683
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
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
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