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Novel neural adaptive terminal sliding mode control for TCP network systems with arbitrary convergence time

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A Correction to this article was published on 21 October 2023

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Abstract

The problem of adaptive arbitrary convergence time terminal sliding mode control (TSMC) for nonlinear networked systems with completely unknown functions and nonresponsive UDP stream disturbances is studied. In this work, an improved sliding surface based on arbitrary convergence time is designed to overcome the issue that the convergence rate depends on the system state. Different from the traditional TSMC, this paper introduces holistically an auxiliary term (nonautonomous differential equation) into the design of a sliding mode controller, which can compensate for the influence of neural adaptive approximation error and ensure the convergence of a closed-loop system at prescribed time. A robust compensation signal is also constructed by introducing a super twisting disturbance observer to process nonresponsive UDP flows. In addition, the controller is designed in a piecewise continuous manner, so that the sliding mode surface can be selected arbitrarily, according to the adaptation after the prescribed time. The effectiveness of the new controller is verified by extensive simulations in comparison with related works.

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Acknowledgements

This work is supported by the National Nature Science Foundation of China under Grant (61873306).

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, People’s Republic of China

    Xuelei Qi, Chen Li & Bao Chen

  2. Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW, 2122, Australia

    Wei Ni

  3. School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, People’s Republic of China

    Hongjun Ma

  4. Key Laboratory of Autonomous Systems and Networked Control, Ministry of Education, Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong, Guangzhou, People’s Republic of China

    Hongjun Ma

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  1. Xuelei Qi
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  2. Chen Li
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  3. Bao Chen
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  4. Wei Ni
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  5. Hongjun Ma
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Correspondence to Hongjun Ma.

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Qi, X., Li, C., Chen, B. et al. Novel neural adaptive terminal sliding mode control for TCP network systems with arbitrary convergence time. Neural Comput & Applic 35, 20365–20374 (2023). https://doi.org/10.1007/s00521-023-08746-z

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  • DOI: https://doi.org/10.1007/s00521-023-08746-z

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