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Adaptive NN dynamic surface control for a class of uncertain non-affine pure-feedback systems with unknown time-delay

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Abstract

Adaptive neural network (NN) dynamic surface control (DSC) is developed for a class of non-affine pure-feedback systems with unknown time-delay. The problems of “explosion of complexity” and circular construction of the practical controller in the traditional backstepping algorithm are avoided by using this controller design method. For removing the requirements on the sign of the derivative of function fi, Nussbaum control gain technique is used in control design procedure. The effects of unknown time-delays are eliminated by using appropriate Lyapunov-Krasovskii functionals. Proposed control scheme guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Two simulation examples are presented to demonstrate the method.

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Author information

Authors and Affiliations

  1. Information Engineering College, Henan University of Science and Technology, Luoyang, 471023, China

    Xiao-Qiang Li & Zhu-Mu Fu

  2. Marine Engineering College, Dalian Maritime University, Dalian, 116026, China

    Dan Wang

Authors
  1. Xiao-Qiang Li
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  2. Dan Wang
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  3. Zhu-Mu Fu
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Corresponding author

Correspondence to Xiao-Qiang Li.

Additional information

This work was partially supported by the Key Program of Henan Provincial Department of Education (No. 13A470254), National Natural Science Foundation of China (Nos. 61273137 and 51375145), the Science and Technology Innovative Foundation for Distinguished Young Scholar of Henan Province (No. 144100510004), and the Science and Technology Programme Foundation for the Innovative Talents of Henan Province University (No. 13HASTIT038).

Recommended by Associate Editor Wing Cheong Daniel Ho

Xiao-Qiang Li graduated in mathematics from Datong University, China in 2004. He received the M. Sc. degree in mathematics from Dalian Maritime University, China in 2007 and the Ph.D. degree in control theory and control engineering from Dalian Maritime University, China in 2011. He is currently an associate professor at Henan of University Science and Technology, China.

His research interests include nonlinear control theory and applications, neural networks, adaptive control.

ORCID iD: 0000-0001-7118-6816

Dan Wang graduated in automation engineering from Dalian University of Technology, China in 1982. He received the M. Sc. degree in marine automation engineering from Dalian Maritime University, China in 1987, and the Ph.D. degree in automation and computer-aided engineering from Chinese University of Hong Kong, China in 2001. He is currently a professor at Dalian Maritime University, China.

His research interests include nonlinear control theory and applications, neural networks, adaptive control, robust control, fault detection and isolation, and system identification.

Zhu-Mu Fu graduated in mechanical design and manufacturing from Luoyang Institute of Technology, China in 1998. He received the M. Sc. degree in vehicle engineering from Henan University of Science and Technology, China in 2003. He received the Ph. D. degree in control theory and control engineering from Southeast University, China in 2007. He is currently an associate professor at Henan University of Science and Technology, China.

His research interests include nonlinear control theory and applications, H-infinity control, energy management strategy for hybrid electric vehicle.

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Li, XQ., Wang, D. & Fu, ZM. Adaptive NN dynamic surface control for a class of uncertain non-affine pure-feedback systems with unknown time-delay. Int. J. Autom. Comput. 13, 268–276 (2016). https://doi.org/10.1007/s11633-015-0924-8

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  • DOI: https://doi.org/10.1007/s11633-015-0924-8

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