Real-time Iterative Learning Control
demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.
Series
Edition
1st ed. Softcover of orig. ed. 2009
Language
Place of publication
Target group
Professional and scholarly
Research
Illustrations
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
ISBN-13
978-1-84996-824-9 (9781849968249)
DOI
10.1007/978-1-84882-175-0
Schweitzer Classification
Professor Jian-Xin Xu received the Bachelor degree from Zhejiang University, China in 1982. He attended the University of Tokyo, Japan, where he received Master's and PhD degrees in 1986 and 1989 respectively. All degrees are in Electrical Engineering. He worked for one year in the Hitachi research Laboratory, Japan; for more than one year in Ohio State University, U.S.A. as a Visiting Scholar; and for 6 months in Yale University as a Visiting Research Fellow. In 1991 Professor Xu joined the National University of Singapore and is currently a professor at Department of Electrical and Computer Engineering. His research interests lie in the fields of intelligent and robust control and applications to motion control, mechatronics, and robotics. He is a Fellow of IEEE.
Up to now he produced more than 500 peer-reviewed journal and conference papers, 2 monographs and 3 edited books. He has been supervising/co-supervising 29 PhD, 20 Master students, and 15 research staff including postdoctoral fellows and research fellows. He has completed 20 funded research projects and currently he work on AUV biomimetic locomotion and control.
Dr Khalid Abidi received his BSc. degree in Mechanical Engineering from the Middle East Technical University, Ankara, Turkey in 2002 and the MSc. degree in Electrical Engineering and Computer Science from Sabanci University, Istanbul, Turkey in 2004. He obtained his PhD degree in Electrical and Computer Engineering, specializing in the area of Control Engineering, from the National University of Singapore in 2009. Dr Abidi is currently a lecturer of Electrical Power Engineering at Newcastle University based in Singapore. Prior to joining Newcastle University Dr Abidi worked as an Assistant Professor of Mechatronics Engineering at Bahcesehir University, Istanbul, Turkey from September 2009 until June 2014. His research interests include: Theory and modelling of dynamical systems, Discrete-Time systems, Time-delay systems, Learning Control, Robust Control, Applied Nonlinear Control, Robotics and Mechatronic Systems.
to ILC: Concepts, Schematics, and Implementation.- Robust Optimal ILC Design for Precision Servo: Application to an XY Table.- ILC for Precision Servo with Input Non-linearities: Application to a Piezo Actuator.- ILC for Process Temperature Control: Application to a Water-heating Plant.- ILC with Robust Smith Compensator: Application to a Furnace Reactor.- Plug-in ILC Design for Electrical Drives: Application to a PM Synchronous Motor.- ILC for Electrical Drives: Application to a Switched Reluctance Motor.- Optimal Tuning of PID Controllers Using Iterative Learning Approach.- Calibration of Micro-robot Inverse Kinematics Using Iterative Learning Approach.- Conclusion.
