Neural networks-based iterative learning control consensus for periodically time-varying multi-agent systems

CHEN JiaXi ¹LI JunMin ¹CHEN WeiSheng ²GAO WeiFeng¹

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作者信息

1. School of Mathematics and Statistics,Xidian University,Xi'an 710071,China
2. School of Aerospace Science and Technology,Xidian University,Xi,an 710071,China
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Abstract

In this paper,the problem of adaptive iterative learning based consensus control for periodically time-varying multi-agent systems is studied,in which the dynamics of each follower are driven by nonlinearly parameterized terms with periodic disturbances.Neural networks and Fourier base expansions are introduced to describe the periodically time-varying dynamic terms.On this basis,an adaptive learning parameter with a positively convergent series term is constructed,and a distributed control protocol based on local signals between agents is designed to ensure accurate consensus of the closed-loop systems.Furthermore,con-sensus algorithm is generalized to solve the formation control problem.Finally,simulation experiments are implemented through MATLAB to demonstrate the effectiveness of the method used.

Key words

multi-agent systems/adaptive iterative learning control/nonlinearly parameterized dynamics/Fourier series expansion/neural networks

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基金项目

National Natural Science Foundation of China(62203342)

National Natural Science Foundation of China(62073254)

National Natural Science Foundation of China(92271101)

National Natural Science Foundation of China(62106186)

National Natural Science Foundation of China(62103136)

Fundamental Research Funds for the Central Universities(XJS220704)

Fundamental Research Funds for the Central Universities(QTZX23003)

Fundamental Research Funds for the Central Universities(ZYTS23046)

China Postdoctoral Science Foundation(2022M712489)

Natural Science Basic Research Program of Shaanxi(2023-JC-YB-585)

Natural Science Basic Research Program of Shaanxi(2020JM-188)

出版年

2024

中国科学:技术科学(英文版)

中国科学院

中国科学:技术科学(英文版)

CSTPCDEI

影响因子：1.056

ISSN：1674-7321

参考文献量43

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