Quantisation compensated data-driven iterative learning control for nonlinear systems-Reference-Cited by-同舟云学术

Quantisation compensated data-driven iterative learning control for nonlinear systems

Published:2021-07-09 Issue:2 Volume:53 Page:275-290
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Zhang Huimin¹²,Chi Ronghu¹²,Hou Zhongsheng³,Huang Biao⁴

Affiliation:

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

2. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China

3. School of Automation, Qingdao University, Qingdao, People's Republic of China

4. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada

Funder

National Science Foundation of China

Taishan Scholar Program of Shandong Province of China

Natural Science Foundation of Shandong Province of China

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2021.1950232

Reference40 articles.

1. Adaptive Iterative Learning Control for Linear Systems With Binary-Valued Observations

2. Quantized Data Driven Iterative Learning Control for a Class of Nonlinear Systems With Sensor Saturation

3. Iterative learning control for discrete‐time systems with quantised measurements

4. Model Free Adaptive Iterative Learning Consensus Tracking Control for a Class of Nonlinear Multiagent Systems

5. Tracking Performance Limitations of MIMO Networked Control Systems With Multiple Communication Constraints

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