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Springer Fuzzy Logic, Identification and Predictive Control

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Description

Modern industrial processes require advanced control protocols that go beyond simple on/off responses. This book from the Advances in Industrial Control series addresses the need for systems capable of handling circumstances that demand judgment rather than just numerical data. Fuzzy systems provide a unique advantage by managing both numeric and linguistic information within a single framework. This capability makes them highly effective for complex industrial environments where linguistic descriptions are often more relevant than rigid numbers. Fuzzy Logic, Identification and Predictive Control guides readers through the construction of static and dynamic fuzzy models. By using numerical data from various real-world applications, the text provides a practical approach to understanding how fuzzy logic can be applied to identification and predictive control in modern systems.

Key Features

Learn to construct both static and dynamic fuzzy models using real-world numerical data.

Understand how to integrate linguistic descriptions with numerical information for better system control.

Explore advanced control protocols designed for complex industrial processes and systems.

Gain knowledge on using fuzzy systems to handle circumstances requiring judgment instead of simple on/off responses.

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

Product Specifications

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

Barcode

No barcode data available

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