Adaptive Consensus Quantized Control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints-Reference-Cited by-同舟云学术

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Adaptive Consensus Quantized Control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints

Published:2022-09 Issue:9 Volume:9 Page:1574-1589
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Zhu Guoqiang¹,Li Haoqi¹,Zhang Xiuyu¹,Wang Chenliang²,Su Chun-Yi³,Hu Jiangping⁴

Affiliation:

1. School of Automation Engineering, Northeast Electric Power University,Jilin,132012

2. School of Automation Science and Electrical Engineering, Beihang University,Beijing,China,100191

3. Concordia University,Department of Mechanical and Industrial Engineering,Montreal,QC,Canada,H3B 1R6

4. School of Automation Engineering, University of Electronic Science and Technology of China,Chengdu,China,611731

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Control and Optimization

Link

http://xplorestaging.ieee.org/ielx7/6570654/9864997/09865039.pdf?arnumber=9865039

Reference59 articles.

1. Hysteresis inverse compensation-based model reference adaptive control for a piezoelectric micro-positioning platform

2. Neural Network-based Iterative Learning Control for Hysteresis in Magnetic Shape Memory Alloy Actuator

3. Theoretical analysis of the dynamic behavior of hysteresis elements in mechanical systems

4. Modeling of battery dynamics and hysteresis for power delivery prediction and SOC estimation

5. Hysteresis modeling in the MATLAB/Power System Blockset

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