Iterative Learning Control Algorithms and Experimental Benchmarking
Eric Rogers, P. L. Lewin, Christopher Freeman, Bing Chu
Abstract
The book discusses the main methods of iterative learning control (ILC) and its interactions, as well as comparator performance that is so crucial to the end user. The book provides integrated coverage of the major approaches to-date in terms of basic systems, theoretic properties, design algorithms, and experimentally measured performance, as well as the links with repetitive control and other related areas.
Topics & Concepts
BenchmarkingIterative learning controlComputer scienceControl (management)AlgorithmArtificial intelligenceMachine learningBusinessMarketingIterative Learning Control Systems