Advances in Industrial Control

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

Authors: Wang, Danwei, Ye, Yongqiang, Zhang, Bin

  • First book of iterative learning control (ILC) from frequency domain and sampled data methodologies
  • Summarizes the latest study of learning performance and learning stability
  • Maximizes reader insights into the practical significance of ILC with verifications by experiments
  • Written by foremost experts in the field
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eBook $99.00
price for USA (gross)
  • ISBN 978-981-4585-60-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-981-4585-59-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 11, 2016
  • ISBN 978-981-10-1353-9
  • Free shipping for individuals worldwide
Rent the ebook  
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About this book

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.

About the authors

Dr. Danwei Wang received his Ph.D and MSE degrees from the University of Michigan, Ann Arbor in 1989 and 1984, respectively. He received his B.E degree from the South China University of Technology, China in 1982. Now, he is a professor in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He served as head of Division of Control and Instrumentation from 2005 to 2011. He has served as general chairman, technical chairman and various positions in international conferences. He is an associate editor of International Journal of Humanoid Robotics and invited guest editor of various international journals. He was a recipient of Alexander von Humboldt fellowship, Germany. He has published widely in the areas of iterative learning control, repetitive control, fault diagnosis and failure prognosis, satellite formation dynamics and control, as well as manipulator/mobile robot dynamics, path planning, and control.

Dr. Yongqiang Ye received the B.E. and MEng degrees in electrical engineering from Zhejiang University, China, in 1994 and 1997, respectively, and the Ph.D. degree in electrical engineering from Nanyang Technological University, Singapore, in 2004. From 2006, he had been a Postdoctoral Research Fellow for 3 years in Canada with Lakehead University, Carleton University, and Dalhousie University, respectively. Since 2009, he has been a Professor with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. He has authored or coauthored more than 24 international journal papers. His research interests include iterative learning control and repetitive control, power electronics control, and image processing. He is a senior member of IEEE.

Dr. Bin Zhang received the B.E. and M.E. degrees from Nanjing University of Science and Technology, Nanjing, China, in 1993 and 1999, respectively,  both in Mechanical Engineering, and the Ph.D. degree in Electrical Engineering from Nanyang Technological University, Singapore, in 2005. After his graduation, he joined the School of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA as a post-doc research fellow. In 2009, he joined Impact Technologies, LLC, Rochester, NY as a senior project engineer and later lead engineer. Then, he joined the R&D of General Motors, Detroit, MI as a senior researcher in 2011. Since 2012, he has been an Assistant Professor in the Department of Electrical Engineering at the University of South Carolina, Columbia, SC.  He has about 15 years experience in dynamics and control, intelligent systems, mechatronics, prognostics and health management. He has authored and co-authored more than 80 papers in areas of his expertise. He is currently an Associate Editor for IEEE Transactions on Industrial Electronics, International Journal of Fuzzy Logic and Intelligent Systems. He is a senior member of IEEE.

Table of contents (9 chapters)

  • Introduction

    Wang, Danwei (et al.)

    Pages 1-24

  • Learnable Band Extension and Multi-channel Configuration

    Wang, Danwei (et al.)

    Pages 25-51

  • Learnable Bandwidth Extension by Auto-Tunings

    Wang, Danwei (et al.)

    Pages 53-73

  • Reverse Time Filtering Based ILC

    Wang, Danwei (et al.)

    Pages 75-102

  • Wavelet Transform Based Frequency Tuning ILC

    Wang, Danwei (et al.)

    Pages 103-126

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-981-4585-60-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-981-4585-59-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: November 11, 2016
  • ISBN 978-981-10-1353-9
  • Free shipping for individuals worldwide
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation
Authors
Series Title
Advances in Industrial Control
Copyright
2014
Publisher
Springer Singapore
Copyright Holder
Springer Science+Business Media Singapore
eBook ISBN
978-981-4585-60-6
DOI
10.1007/978-981-4585-60-6
Hardcover ISBN
978-981-4585-59-0
Softcover ISBN
978-981-10-1353-9
Series ISSN
1430-9491
Edition Number
1
Number of Pages
XII, 226
Number of Illustrations and Tables
42 b/w illustrations, 120 illustrations in colour
Topics