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International Symposium on Neural Networks

ISNN 2017: Advances in Neural Networks - ISNN 2017 pp 44–51Cite as

Approximation-Based Adaptive Neural Tracking Control of an Uncertain Robot with Output Constraint and Unknown Time-Varying Delays

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

Abstract

This paper presents an adaptive neural control design for an n-link rigid robot with both output constraint and unknown time-varying delays. The main design difficulties caused by both the output constraint and unknown time-varying delayed states. In order to overcome these difficulties, the novel Barrier Lyapunov Functions (BLF) and iterative backstepping procedures are employing to guarantee constraints satisfaction of the position of the robot. The Lyapunov-krasovskii functionals (LKFs) are utilized to eliminate and compensate the effect of unknown functions with time-varying delayed states in communication channels. By using the Lyapunov analysis, the stability of closed-loop systems is proven.

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Acknowledgements

The work is supported by the National Natural Science Foundation of China (61473139, 61622303 and 61603164), the Doctoral Scientific Research Staring Fund of Binzhou University under Grant 2016Y14 and the project for Distinguished Professor of Liaoning Province.

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Authors and Affiliations

  1. School of Electrical Engineering, Liaoning University of Technology, Jinzhou, 121001, China

    Da-Peng Li

  2. College of Science, Liaoning University of Technology, Jinzhou, 121001, China

    Yan-Jun Liu & Shaocheng Tong

  3. School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou, 121001, China

    Dong-Juan Li & Duo Meng

  4. Department of Mathematics, Binzhou University, Binzhou, 256600, China

    Guo-Xing Wen

Authors
  1. Da-Peng Li
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  2. Yan-Jun Liu
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  3. Dong-Juan Li
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  4. Shaocheng Tong
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  5. Duo Meng
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  6. Guo-Xing Wen
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Corresponding author

Correspondence to Da-Peng Li .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Li, DP., Liu, YJ., Li, DJ., Tong, S., Meng, D., Wen, GX. (2017). Approximation-Based Adaptive Neural Tracking Control of an Uncertain Robot with Output Constraint and Unknown Time-Varying Delays. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-59081-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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