Iterative Learning Control : Robustness and Monotonic Convergence for Interval Systems
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 iteration-domain stochastic uncertainty.
كتب مشابهة
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Covers innovations in the field of composite materials with a specific focus on eco-friendly and environmentally sustainable systems. All composite fields are explored, including polymer, metal, and ceramic matrix composites with an emphasis on sourcing raw materials in a sustainable way as well as the development of composite materials for environmental sustainability.
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