Correction: Bai et al. Containment Control of Fractional-Order Time-Delay Multi-Agent Systems Employing a Fully Distributed Pull-Based Event-Triggered Approach. Fractal Fract. 2025, 9, 658

1. Text Correction

There was an error in the original publication [1]. The use of different versions of reference management software (e.g., EndNote/Zotero) by the collaborating authors led to formatting inconsistencies and missing entries when the final document was compiled. Therefore, the references need to be updated, and the mentions in the text also need to be updated.

A correction has been made to Introduction, Paragraph 3:

Recent studies reflect increasing focus on containment control within fractional-order multi-agent systems (FOMASs), with foundational contributions emerging in this domain [18–21]. In [18,19], Liu et al. established necessary and sufficient conditions for achieving containment in FOMASs with time-varying delays. In [20], Pang et al. developed both nondelayed and delayed communication protocols for nonlinear FOMASs by leveraging fractional-order Razumikhin methods. A common feature of these approaches is their exclusive reliance on continuous state feedback. Practical implementation challenges arise, however, from the persistent requirement for agents to acquire neighbors’ state data via communication networks. This process not only strains communication bandwidth but also imposes considerable computational loads on onboard sensors and processing units. To address these operational constraints, this study proposes novel practical and resource-efficient control strategies for FOMASs that explicitly overcome the limitations of continuous communication and computational burden.

The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

2. References from Publication [1]

6.

Li, Y.; Park, J.; Hua, C.; Liu, G. Distributed adaptive output feedback containment control for time-delay nonlinear multiagent systems. Automatica 2021, 127, 109545. https://doi.org/10.1016/j.automatica.2021.109545.

7.

Liu, T.; Hou, Z. Model-Free Adaptive Containment Control for Unknown Multi-Input Multi-Output Nonlinear MASs With Output Saturation. IEEE Trans. Circuits Syst. I 2023, 70, 2156–2166. https://doi.org/10.1109/TCSI.2023.3242677.

8.

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9.

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Yao, Y.; Yuan, J.; Chen, T.; Zhang, C.; Yang, H. Adaptive Neural Control for a Class of Random Fractional-Order Multi-Agent Systems with Markov Jump Parameters and Full State Constraints. Fractal Fract. 2024, 8, 278. https://doi.org/10.3390/fractalfract8050278.

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Li, W.; Shi, L.; Shi, M.; Yue, J.; Lin, B.; Qin, K. Analyzing Containment Control Performance for Fractional-order Multi-Agent Systems via A Delay Margin Perspective. IEEE Trans. Netw. Sci. Eng. 2024, 11, 2810–2821. https://doi.org/10.1109/TNSE.2024.3350122.

20.

Pang, D.; Liu, X.; Zhao, X. Containment control analysis of delayed nonlinear fractional-order multi-agent systems. Math. Methods Appl. Sci. 2024, 48, 1. https://doi.org/10.1002/mma.10354.

22.

Shi, L.; Li, W.; Shi, M.; Lin, B. Event-Based Bipartite Containment Control for Multi-Agent Networks Subject to Communication Delay. IEEE Trans. Netw. Sci. Eng. 2023, 11, 2024–2033. https://doi.org/10.1109/TNSE.2023.3336363.

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Hernández-González, O.; Targui, B.; Valencia-Palomo, G.; Guerrero-Sánchez, M. Robust cascade observer for a disturbance unmanned aerial vehicle carrying a load under multiple time-varying delays and uncertainties. Int. J. Syst. Sci. 2024, 55, 1056–1072. https://doi.org/10.1080/00207721.2023.2301496.

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The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.