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Robust Control Design of Uncertain Strict Feedback Systems Using Adaptive Filters

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Advances in Neural Networks – ISNN 2018 (ISNN 2018)

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Abstract

This paper concerns on the tracking problem of uncertain strict feedback systems. By employing the adaptive filters, a robust state feedback control scheme is derived, where a common compensator is utilized to eliminate the effects induced by each filters. Compared with the existing results using standard dynamic surface control approach, the closed loop stability does not depend on small filter time constants. Finally, the correctness of the developed methodology is demonstrated via a numerical example.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant No. 61733006.

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Authors and Affiliations

  1. Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, 510640, Guangdong, People’s Republic of China

    Yong-Hua Liu & Chun-Yi Su

Authors
  1. Yong-Hua Liu
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  2. Chun-Yi Su
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Corresponding author

Correspondence to Yong-Hua Liu .

Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

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Liu, YH., Su, CY. (2018). Robust Control Design of Uncertain Strict Feedback Systems Using Adaptive Filters. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_87

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  • DOI: https://doi.org/10.1007/978-3-319-92537-0_87

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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