Details

Autor(en) / Beteiligte

• Guo, Zirong
• Meng, Deyuan

Titel

Disturbance Observer-Based Design and Analysis of Iterative Learning Control with Nonrepetitive Uncertainties

Ist Teil von

• Proceedings of 2020 Chinese Intelligent Systems Conference, 2020, Vol.705, p.739-748

Ort / Verlag

Singapore: Springer Singapore Pte. Limited

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper considers a general nonsquare multi-input, multi-output iterative learning control (ILC) system with bounded uncertainties, and proposes a disturbance observer-based ILC method. It is shown that ILC with a disturbance observer has a better performance than traditional ILC against nonrepetitive uncertainties. Numerical examples are provided to illustrate the proposed robust ILC conclusions.