Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems

Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems
Автор
 
Год
 
Страниц
 
230
ISBN
 
1846288460
Издатель
 
Springer

Описание:

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 knowledge of the system to be controlled and; second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergence is often essential. "Iterative Learning Control" takes account of the recently-developed comprehensive approach to robust ILC analysis and design established to handle the situation where the plant model is uncertain. Considering ILC in the iteration domain, it presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and...

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