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Springer - Iterative Learning Control Monograph Book

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Description

This technical monograph by Springer provides an in-depth study of the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Iterative learning control (ILC) is a highly efficient method for improving performance in systems that operate through repetitive processes, such as industrial batch processes or robot arms in manufacturing environments. While the fundamentals of ILC design are established in existing literature, this work addresses two significant challenges currently being researched in the field. It specifically focuses on overcoming the limitations found in many existing ILC design strategies that rely on nominal knowledge. By exploring robustness and monotonic convergence for interval systems, this book offers valuable insights for engineers and researchers working with repetitive systems that require high-performance precision.

Key Features

Focuses on the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems.

Addresses key research gaps in ILC design, specifically moving beyond strategies that assume only nominal knowledge.

Provides specialized knowledge for managing interval systems within an iterative learning control framework.

Applicable to practical industrial settings including manufacturing robot arms and repetitive batch processes.

Part of the Communications and Control Engineering series from Springer.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
26 June 2007
Listed Since
19 February 2007

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