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Estimation of and compensation for unknown input nonlinearities using equivalent-input-disturbance approach

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Abstract

Nonlinearities greatly affect the control performance of a system. A new estimation and compensation method for unknown input dead zone and backlash has been developed based on the equivalent-input-disturbance (EID) approach. Unlike other methods, it requires neither any information on the nonlinearities nor an inverse model of them. The key idea is that input nonlinearities are taken to be an input-dependent disturbance. An EID estimator is designed that produces an estimate with the same effect on the output as that of the input nonlinearities. The estimate is then used to compensate for the nonlinearities. Simulation results demonstrate the validity of the method.

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Acknowledgements

The authors would like to thank Professor Chuanke Zhang of China University of Geosciences and Dr. Fang Gao of Central South University for their constructive comments and suggestions, which have improved the quality and readability of this paper.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, Hunan, 410083, China

    Liyu Ouyang

  2. School of Automation, China University of Geosciences, Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan, Hubei, 430074, China

    Min Wu & Jinhua She

  3. School of Engineering, Tokyo University of Technology, Hachioji, Tokyo, 192-0982, Japan

    Jinhua She

Authors
  1. Liyu Ouyang
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  2. Min Wu
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  3. Jinhua She
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Corresponding author

Correspondence to Jinhua She.

Additional information

This work was supported by the National Natural Science Foundation of China under Grants 61473313 and 61210011, the Hubei Provincial Natural Science Foundation of China under Grant 2015CFA010, and the 111 Project of China under Grant B17040.

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Ouyang, L., Wu, M. & She, J. Estimation of and compensation for unknown input nonlinearities using equivalent-input-disturbance approach. Nonlinear Dyn 88, 2161–2170 (2017). https://doi.org/10.1007/s11071-017-3369-5

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  • DOI: https://doi.org/10.1007/s11071-017-3369-5

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