Iterative learning control (ILC) Arimoto et al. 1984 was originally proposed as an intelligent learning mechanism for robot manipulators. Many ILC methods have been developed and widely applied to achieve perfect tracking performance by repeating the tracking task with learning. In general, the ILC methods can be classified into three categories according to the design and analysis methods, i.e., contraction mapping (CM)-based ILC (CM-ILC), composite energy function (CEF)-based ILC (CEF-ILC), and normal optimization-based ILC (NOILC).
Compact Form Iterative Dynamic Linearation Based DDILC
Intelligent Control & Learning Systems
Data-Driven Iterative Learning Control for Discrete-Time Systems ; Chapter : 2 ; 15-29
2022-11-16
15 pages
Article/Chapter (Book)
Electronic Resource
English
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