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Adaptive neural control of unknown non-affine nonlinear systems with input deadzone and unknown disturbance

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Abstract

In this paper, an adaptive neural scheme is developed for unknown non-affine nonlinear systems with input deadzone and internal/external unknown disturbance. With the help of mean value theorem and implicit function theorem, the control problem that the system input cannot be expressed in a linear form can be solved. The unknown input deadzone is approximated by neural networks. The immeasurable states are estimated by a high-gain observer such that output feedback control is obtained. The approximation error of both neural networks and the unknown internal/external disturbance is considered as an overall disturbance which is compensated by a novel disturbance observer. Via Lyapunov’s stability theory, it can be proved that all the state signals are uniformly bounded ultimately. The transient response performance can be improved by tuning the control parameters, and the steady-state error converges to any small neighborhood of zero. Simulation examples are carried out to verify the effectiveness of the proposed method.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants 61873297 and 61873206 and 61622308 and Science and Technology on Space Intelligent Control Laboratory (ZDSYS-2017-05) and the Fundamental Research Funds for the China Central Universities of USTB under Grant FRF-BD-17-002A and China Postdoctoral Science Foundation funded Project No. 2018M630074 and Fundamental Research Funds of Shenzhen Science and Technology Project (JCYJ20160229172341417).

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Authors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Shuang Zhang, Linghuan Kong, Peng Jing & Wei He

  2. Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, 100083, China

    Shuang Zhang, Linghuan Kong, Peng Jing & Wei He

  3. Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, 518060, China

    Suwen Qi

  4. Research Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China

    Bin Xu

  5. School of Automation, Northwestern Polytechnical University, Xi’an, 710072, China

    Bin Xu

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  1. Shuang Zhang
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Correspondence to Wei He.

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Zhang, S., Kong, L., Qi, S. et al. Adaptive neural control of unknown non-affine nonlinear systems with input deadzone and unknown disturbance. Nonlinear Dyn 95, 1283–1299 (2019). https://doi.org/10.1007/s11071-018-4629-8

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