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© 2020

Iterative Learning Control for Flexible Structures

Book

Part of the Springer Tracts in Mechanical Engineering book series (STME)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Tingting Meng, Wei He
    Pages 1-13
  3. Tingting Meng, Wei He
    Pages 49-82
  4. Tingting Meng, Wei He
    Pages 109-128
  5. Tingting Meng, Wei He
    Pages 129-152
  6. Tingting Meng, Wei He
    Pages 153-180
  7. Tingting Meng, Wei He
    Pages 181-182

About this book

Introduction

This book presents iterative learning control (ILC) to address practical issues of flexible structures. It is divided into four parts: Part I provides a general introduction to ILC and flexible structures, while Part II proposes various types of ILC for simple flexible structures to address issues such as vibration, input saturation, input dead-zone, input backlash, external disturbances, and trajectory tracking. It also includes simple partial differential equations to deal with the common problems of flexible structures. Part III discusses the design of ILC for flexible micro aerial vehicles and two-link manipulators, and lastly, Part IV offers a summary of the topics covered.
 
Unlike most of the literature on ILC, which focuses on ordinary differential equation systems, this book explores distributed parameter systems, which are comparatively less stabilized through ILC.
Including a comprehensive introduction to ILC of flexible structures, it also examines novel approaches used in ILC to address input constraints and disturbance rejection.
 
This book is intended for researchers, graduate students and engineers in various fields, such as flexible structures, external disturbances, nonlinear inputs and tracking control.

Keywords

Iterative learning control Flexible structures Distributed parameter systems Nonlinear inputs Disturbance rejection Trajectory tracking Micro aerial vehicle Flexible manipulators

Authors and affiliations

  1. 1.Academy of Mathematics and Systems ScienceBeijingChina
  2. 2.University of Science and Technology BeijingBeijingChina

About the authors

Professor Wei He received his PhD from school of Electrical & Computer Engineering, the National University of Singapore (NUS), Singapore, in 2011. He is currently working as full professor at School of Automation and Electric Engineering, University of Science and Technology Beijing (USTB), China. He is a senior member of IEEE. He was awarded a Newton Advanced Fellowship from the Royal Society, UK in 2017. He is the Chair of IEEE SMC Society Beijing Capital Region Chapter. He is serving as the Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Control Systems Technology, IEEE/CAA Journal of Automatica Sinica and Journal of Intelligent & Robotic Systems. His current research interests include robotics, distributed parameter systems and intelligent control systems.


Tingting Meng received her B.Eng. degree in Henan Polytechnic University (HPU), China, in 2014 and received her master degree in control engineering in University of Electronic Science and Technology of China (UESTC), China, in 2017. She is currently a PhD candidate in Academy of Mathematics and Systems Science. She has published 13 SCI papers and her current research interests include iterative learning control, boundary control and distributed parameter systems.

Bibliographic information