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Adaptive control for the nonlinear event-triggered networked control system: a decoupling method

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Abstract

In this paper, the adaptive control for a kind of nonlinear system over the event-driven sensors-controller communication network is addressed. Over this network, the existing strategy has been developed. However, the event-triggered mechanism and adaptive estimators are coupled together, which results in extra information delivery of the adaptive estimators over the network or extra computation equipment on the sensor side. To overcome this limitations, two kinds of adaptive control strategies are proposed in this paper. At first, the control strategy with the new event-triggered adaptive estimator is developed for the system without external disturbances where the event-triggered mechanism does not need the information of the adaptive estimators. It is proved that the closed-loop system is asymptotically stable and the Zeno behaviour is excluded. Furthermore, for the system with external disturbances, a robust control scheme with modified adaptive estimator and event-triggered mechanism is proposed and the practical stability of the closed-loop system is guaranteed. Also, the Zeno behaviour is excluded carefully. Comparing with the existing results, due to the decoupling structure of event-triggered mechanism and adaptive estimators, it is unnecessary to transfer the estimators’ information to the event-triggered mechanism on the sensor side, which saves the communication cost. What’s more, although the system state is sampled and event driven, the asymptotical stability is still guaranteed. Also, the developed strategy can handle with the external disturbances. Finally, two examples are performed to illustrate the effectiveness of the schemes and some comparisons are displayed to explain the advantages of the methods.

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Availability of data and materials

The datasets generated during and/or analysed during the current study are generated via simulation code which is available in [Adaptive-NCS] repository, [https://github.com/ChaoMpc/Adaptive-NCS].

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Acknowledgements

We would like to express our gratitude to the editor and reviewers for their time and remarkable suggestions to improve the quality of the manuscript. This work was supported by the National Natural Science Foundation of China [Grant Numbers 62003254, 61877046] and the Fundamental Research Funds for the Central Universities, China [Grant Number JB210710].

Funding

Funding This work was supported by the National Natural Science Foundation of China [Grant Numbers. 62003254, 61877046] and the Fundamental Research Funds for the Central Universities, China [Grant Number JB210710].

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Author notes

  1. Sanyang Liu, Junmin Li and Jiaxian Wang have contributed equally to this work.

Authors and Affiliations

  1. School of Mathematics and Statistics, Xidian University, Xi Feng Road, Xi’an, 710126, Shaanxi, China

    Chao He, Sanyang Liu, Junmin Li & Jiaxian Wang

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  1. Chao He
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  2. Sanyang Liu
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [CH], [SL], [JL] and [JW]. The first draft of the manuscript was written by [CH], and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Chao He.

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The simulation code of the presented algorithms are available in [Adaptive-NCS] repository, [https://github.com/ChaoMpc/Adaptive-NCS].

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He, C., Liu, S., Li, J. et al. Adaptive control for the nonlinear event-triggered networked control system: a decoupling method. Nonlinear Dyn 111, 3411–3432 (2023). https://doi.org/10.1007/s11071-022-08010-4

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