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Adaptive Output Feedback Control of Nonlinear Systems with States and Input Unmodeled Dynamics

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Proceedings of the 2015 Chinese Intelligent Automation Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 337))

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Abstract

In this paper, an adaptive output feedback neural control strategy is investigated for a class of nonlinear systems with states and input unmodeled dynamics based on dynamics surface control method. States unmodeled dynamics is described by introducing a kind of Lyapunov function, and the nonlinear input unmodeled dynamics is dealt with by using a normalization signal. The unknown control gain sign is solved with the help of Nussbaum function. By the theoretical analysis, all the signals in the closed-loop system are proved to be semi-globally uniformly ultimately bounded. A numerical example is provided to illustrate the effectiveness of the proposed approach.

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Acknowledgments

This work was partially supported by the National Natural Science Foundation of China (61174046 & 61473250).

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Authors and Affiliations

  1. Department of Automation, College of Information Engineering, Yangzhou University, Yangzhou, 225127, China

    Xiaonan Xia, Tianping Zhang & Qin Wang

Authors
  1. Xiaonan Xia
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  2. Tianping Zhang
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  3. Qin Wang
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Corresponding author

Correspondence to Tianping Zhang .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Zhidong Deng

  2. Department of Computer Science and Techn, Tsinghua University, Beijing, China

    Hongbo Li

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Xia, X., Zhang, T., Wang, Q. (2015). Adaptive Output Feedback Control of Nonlinear Systems with States and Input Unmodeled Dynamics. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46463-2_39

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  • DOI: https://doi.org/10.1007/978-3-662-46463-2_39

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46462-5

  • Online ISBN: 978-3-662-46463-2

  • eBook Packages: EngineeringEngineering (R0)

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