Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation


Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation

Description

This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.


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Details

Author(s)
Danwei Wang, Yongqiang Ye, Bin Zhang
Format
Hardback | 226 pages
Dimensions
155 x 235 x 14.22mm | 4,853g
Publication date
08 Jul 2014
Publisher
Springer Verlag, Singapore
Publication City/Country
Singapore, Singapore
Language
English
Edition Statement
2014 ed.
Illustrations note
120 Illustrations, color; 42 Illustrations, black and white; XII, 226 p. 162 illus., 120 illus. in color.
ISBN10
9814585599
ISBN13
9789814585590