International Journal of Robust and Nonlinear Control

RESEARCH ARTICLE

An iterative learning approach to formation control of discrete-time multi-agent systems With varying trial lengths

Corresponding Author

Yang Liu

[email protected]

orcid.org/0000-0002-0139-9573

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

Correspondence Yang Liu, The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), 37 Xueyuan Road, Haidian District, Beijing 100191, P.R. China.

Email: [email protected]

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Yimin Fan,

Yimin Fan

Southwest China Institute of Electronic Technology, Chengdu, P.R. China

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Yichao Ao,

Yichao Ao

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

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Yingmin Jia,

Yingmin Jia

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

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Yang Liu,

Corresponding Author

Yang Liu

[email protected]

orcid.org/0000-0002-0139-9573

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

Email: [email protected]

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Yimin Fan,

Yimin Fan

Southwest China Institute of Electronic Technology, Chengdu, P.R. China

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Yichao Ao,

Yichao Ao

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

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Yingmin Jia,

Yingmin Jia

The Seventh Research Division and School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, P.R. China

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First published: 18 September 2022

https://doi.org/10.1002/rnc.6359

Citations: 1

Abbreviations: ILC, iterative learning control

Funding information: National Basic Research Program of China (973 Program), Grant/Award Number: 2012CB821201; National Natural Science Foundation of China, Grant/Award Numbers: 62073020; 62133001; 61976013; 61520106010

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Abstract

In this article, an iterative learning approach is proposed for the formation control of discrete-time multi-agent systems, where the trial length of each learning iteration is randomly varying. In particular, a modified state error related to the prescribed formation is defined by taking into account the nonuniform actual trial length that could be different from the desired one. Then, a P-type iterative learning protocol is established for switching networks of agents subject to nonuniform trial lengths, and the convergence analyses are given for the fixed and the iteration-varying initial conditions respectively. It shows that through iterative learning, the given formation will be maintained among multiple agents in the entire time interval of one trial. In the end, simulations are done to demonstrate the correctness of the obtained theoretical results.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest for this article.

Open Research

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Volume32, Issue17

25 November 2022

Pages 9332-9346

An iterative learning approach to formation control of discrete-time multi-agent systems With varying trial lengths

Abstract

CONFLICT OF INTEREST

Open Research

DATA AVAILABILITY STATEMENT

REFERENCES

Citing Literature

References

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An iterative learning approach to formation control of discrete-time multi-agent systems With varying trial lengths

Abstract

CONFLICT OF INTEREST

Open Research

DATA AVAILABILITY STATEMENT

REFERENCES

Citing Literature

References

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