𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Iterative Learning Control: Convergence, Robustness and Applications

✍ Scribed by Yangquan Chen, Changyun Wen


Publisher
Springer
Year
1999
Tongue
English
Leaves
208
Series
Lecture Notes in Control and Information Sciences
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


This book provides readers with a comprehensive coverage of iterative learning control. The book can be used as a text or reference for a course at graduate level and is also suitable for self-study and for industry-oriented courses of continuing education.Ranging from aerodynamic curve identification robotics to functional neuromuscular stimulation, Iterative Learning Control (ILC), started in the early 80s, is found to have wide applications in practice. Generally, a system under control may have uncertainties in its dynamic model and its environment. One attractive point in ILC lies in the utilisation of the system repetitiveness to reduce such uncertainties and in turn to improve the control performance by operating the system repeatedly. This monograph emphasises both theoretical and practical aspects of ILC. It provides some recent developments in ILC convergence and robustness analysis. The book also considers issues in ILC design. Several practical applications are presented to illustrate the effectiveness of ILC. The applied examples provided in this monograph are particularly beneficial to readers who wish to capitalise the system repetitiveness to improve system control performance.


πŸ“œ SIMILAR VOLUMES


Iterative learning control: Convergence,
✍ Yangquan Chen PhD, Changyun Wen PhD (eds.) πŸ“‚ Library πŸ“… 1999 πŸ› Springer-Verlag London 🌐 English

<p>This book provides readers with a comprehensive coverage of iterative learning control. The book can be used as a text or reference for a course at graduate level and is also suitable for self-study and for industry-oriented courses of continuing education.<BR>Ranging from aerodynamic curve ident

Iterative Learning Control: Robustness a
✍ Hyo-Sung Ahn, Kevin L. Moore, YangQuan Chen πŸ“‚ Library πŸ“… 2007 πŸ› Springer 🌐 English

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledg

Iterative Learning Control: Robustness a
✍ Hyo-Sung Ahn PhD, YangQuan Chen PhD, Kevin L. Moore PhD, PE (auth.) πŸ“‚ Library πŸ“… 2007 πŸ› Springer-Verlag London 🌐 English

<p><P>This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal kn

Iterative Learning Control: Robustness a
✍ Hyo-Sung Ahn, Kevin L. Moore, YangQuan Chen πŸ“‚ Library πŸ“… 2007 🌐 English

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including p

Real-time Iterative Learning Control: De
✍ Jian-Xin Xu, Sanjib K. Panda, Tong Heng Lee (auth.) πŸ“‚ Library πŸ“… 2009 πŸ› Springer-Verlag London 🌐 English

<p><P>Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.</P><P><EM>Real-time Iterative Learning Contro

Iterative Learning Control: Analysis, De
✍ Suguru Arimoto (auth.), Zeungnam Bien, Jian-Xin Xu (eds.) πŸ“‚ Library πŸ“… 1998 πŸ› Springer US 🌐 English

<p>Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informaΒ­ tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in I