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A modular designed bolt tightening shaft based on adaptive fuzzy backstepping control

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  • Control Theory and Applications
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Abstract

This paper presents a modular designed autonomous bolt tightening shaft system with an adaptive fuzzy backstepping control approach developed for it. The bolt tightening shaft is designed for the autonomous bolt tightening operation, which has huge potential for industry application. Due to the inherent nonlinear and uncertain properties, the bolt tightening shaft and the bolt tightening process are mathematically modeled as an uncertain strict feedback system. With the adaptive backstepping and approximation property of fuzzy logic system, the controller is recursively designed. Based on the Lyapunov stability theorem, all signals in the closed-loop system are proved to be uniformly ultimately bounded and the torque tracking error exponentially converges to a small residue. And the effectiveness and performance of the proposed autonomous system are verified by the simulation and experiment results on the bolt tightening shaft system.

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Author information

Authors and Affiliations

  1. School of Automation Engineering, and Center for Robotics, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Sibang Liu

  2. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

  3. Center for Robotics, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Shuzhi Sam Ge

  4. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Zhongliang Tang

Authors
  1. Sibang Liu
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  2. Shuzhi Sam Ge
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  3. Zhongliang Tang
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Corresponding author

Correspondence to Sibang Liu.

Additional information

Recommended by Associate Editor Pinhas Ben-Tzvi under the direction of Editor Euntai Kim.

Sibang Liu received the B.E. and M.E. degrees from the Hefei University of Technology, Hefei, China, in 2005 and 2010, respectively. He is currently pursuing the Ph.D. degree with the Center for Robotics, School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China. His current research interests include robotic intelligence and adaptive systems.

Shuzhi Sam Ge received the B.Sc. degree from Beijing University of Aeronautics andAstronautics, Beijing, China, in 1986, and the Ph.D. degree from Imperial College, London, U.K., in 1993. He is the Founding Director with the Social Robotics Laboratory of Interactive Digital Media Institute, a Professor with the Department of Electrical and Computer Engineering, the National University of Singapore, Singapore, and Director of Center for Robotics, University of Electronic Science and Technology of China, Chengdu, China. He has authored or coauthored five books and over 300 international journal and conference papers. He is the Editor-in-Chief of the International Journal of Social Robotics. He has served/been serving as an Associate Editor for a number of flagship journals. His current research interests include robotics and intelligent systems. Dr. Ge is a Fellow of Institute of Electrical and Electronics Engineers (IEEE), International Federation of Automatic Control (IFAC) and The Institution of Engineering and Technology (IET), U.K.

Zhongliang Tang received the B.Eng degree in automatic control from the University of Electronic Science and Technology of China, Chengdu, China in 2011. He is currently pursuing the Ph.D. degree with the School of Computer Science and Engineering in the same university. His current research interests include the constrained nonlinear systems, intelligent robotic systems and artificial intelligence.

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Liu, S., Ge, S.S. & Tang, Z. A modular designed bolt tightening shaft based on adaptive fuzzy backstepping control. Int. J. Control Autom. Syst. 14, 924–938 (2016). https://doi.org/10.1007/s12555-015-0008-0

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  • DOI: https://doi.org/10.1007/s12555-015-0008-0

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