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Springer - Iterative Learning Control: Analysis and Design

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Description

Explore the specialized field of Iterative Learning Control (ILC) with this comprehensive text from Springer. Unlike many standard control methods, ILC focuses on maximizing efficiency by using past control information, including tracking errors and control input signals, to build the present control action. This book explains the two essential phases of the ILC process. First, it covers how long term memory components are utilized to store vital past control data. Second, it details how that stored information is fused to ensure systems meet specific control requirements like convergence and robustness. This resource is designed for those studying or working within the realms of AI, Machine Learning, and Computer Science who need a deep understanding of how past data can improve current system performance.

Key Features

Learn how ILC utilizes past control information, such as tracking errors and input signals, to improve present control actions.

Understand the two-phase approach involving long term memory components for storing historical control data.

Gain knowledge on how stored information is fused to meet essential control specifications.

Study methods for ensuring system performance regarding convergence and robustness.

Provides technical insights relevant to AI, Machine Learning, and advanced computer science applications.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
12 October 2012
Listed Since
03 March 2013

Barcode

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