Data‐driven terminal iterative learning control with high‐order learning law for a class of non‐linear discrete‐time multiple‐input–multiple output systems-Reference-Cited by-同舟云学术

Data‐driven terminal iterative learning control with high‐order learning law for a class of non‐linear discrete‐time multiple‐input–multiple output systems

Published:2015-04 Issue:7 Volume:9 Page:1075-1082
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

Chi Ronghu¹,Liu Yu¹,Hou Zhongsheng²,Jin Shangtai²

Affiliation:

1. School of Automation & Electronic Engineering, Qingdao University of Science TechnologyQingdao266042People's Republic of China

2. School of Electronics Information Engineering, Beijing Jiaotong UniversityBeijing100044People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cta.2014.0754

Reference33 articles.

1. Iterative Learning Control for Final Batch Product Quality Using Partial Least Squares Models

2. Terminal iterative learning control with an application to RTPCVD thickness control

3. Bettering operation of Robots by learning

4. Iterative learning model predictive control for multi-phase batch processes

5. Single-cycle and multi-cycle generalized 2D model predictive iterative learning control (2D-GPILC) schemes for batch processes

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