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Springer Practical Grey-box Process Identification Book

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Description

In the field of process modelling, researchers often face challenges where knowledge of a process is only partial and subject to significant disturbances. These disturbances can prevent models from being reproducible. This book provides a solution through grey-box identification, a method that utilizes both invariant prior knowledge and experimental response data. Practical Grey-box Process Identification is structured into three distinct parts to guide the reader through complex concepts. The first part offers a review of the theoretical fundamentals of grey-box identification. It focuses specifically on the theory required for software pre-processing and model development. Part of the Advances in Industrial Control series, this text is designed for those needing to bridge the gap between theoretical knowledge and practical application in industrial control environments.

Key Features

Combines invariant prior knowledge with experimental response data to improve model accuracy and reliability.

Addresses common modeling challenges such as partial process knowledge and significant environmental disturbances.

Structured in three comprehensive parts to facilitate a logical learning progression from theory to application.

Provides a foundational review of theoretical fundamentals necessary for effective software pre-processing.

Part of the professional Advances in Industrial Control series from Springer for advanced technical study.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
21 October 2010
Listed Since
01 October 2010

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