Iterative Learning Control for Flexible Structures
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. Les mer
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Vår pris:
2025,-
(Innbundet)
Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.
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.
Introduction.- Boundary Iterative Learning Control.- ILC for the Vibration Suppression in the Transverse Motion and Rotation.-
ILC for the Nonlinearities of Differentiable and Non-Differentiable Inputs.- ILC for the Rejection of Time-Varying and Spatiotemporally
Varying Disturbances.- Adaptive ILC for an Euler-Bernoulli Beam with Uncertainties.- ILC for Constant and Varying Trajectories
Tracking.- ILC for a Flapping Wing Micro Aerial Vehicle.- ILC for a Flexible Two-Link Manipulator with PDE Model.- Conclusions.
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.
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.