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Observer-Based Adaptive NN Control for Uncertain Nonlinear Systems with Prescribed Performance and Fuzzy Dead-Zone Input

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Abstract

This paper addresses the issue of adaptive prescribed performance control for a category of uncertain nonlinear systems with fuzzy dead-zone input. Through employing the neural networks (NNs) and designing a state observer, the unknown functions and unmeasured system states are approximated, respectively. The problem of fuzzification caused from dead-zone input is handled via using the center-of-gravity theorem. Then, an integrated fuzzy controller is constructed by adopting integrated design approach. It is proved that the proposed integrated fuzzy controller can ensure that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a prescribed domain. Finally, some simulation results are shown to demonstrate feasibility of the presented method.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (61703051) and the Project of Liaoning Province Science and Technology Program under Grant (2019-KF-03-13).

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Authors and Affiliations

  1. School of Mathematics and Physics, Bohai University, Jinzhou, 121013, Liaoning, China

    Wen Yang

  2. College of Engineering, Bohai University, Jinzhou, 121013, Liaoning, China

    Yingnan Pan & Hongjing Liang

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  1. Wen Yang
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Correspondence to Yingnan Pan.

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Yang, W., Pan, Y. & Liang, H. Observer-Based Adaptive NN Control for Uncertain Nonlinear Systems with Prescribed Performance and Fuzzy Dead-Zone Input. Circuits Syst Signal Process 40, 572–597 (2021). https://doi.org/10.1007/s00034-020-01490-y

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