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Více informací o knize Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control

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Anotace knihy

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, moving through classical methods and gradually 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 to the persons working in different disciplines in academics, research and industry in areas concerning to process monitoring, diagnosis, control and related disciplines. Because of its features and systematic presentation of the information content from concepts to advances, anyone can learn and advance their knowledge in their respective domains.  Describes various classical and advanced versions of mechanistic model-based state estimation algorithmsDescribes various data-driven model-based state estimation techniquesHighlights a number of real applications of mechanistic model-based and data-driven model-based state estimators/soft sensors

Parametry knihy

Zařazení knihy Knihy v angličtině Technology, engineering, agriculture Industrial chemistry & manufacturing technologies Industrial chemistry

• Plný název: Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control
• Autor: Ch. Venkateswarlu, Rama Karri
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 366
• EAN: 9780323858786
• ID: 36616967
• Nakladatelství: Elsevier - Health Sciences Division
• Hmotnost: 1074 g
• Rozměry: 216 × 275 × 24 mm
• Datum vydání: 04. February 2022

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