Neural Network-Based Adaptive Dynamic Surface Control for Inverted Pendulum System

  • Enping Wei
  • Tieshan Li
  • Junfang Li
  • Yancai Hu
  • Qiang Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 215)


In this paper, a novel neural network (NN)-based adaptive dynamic surface control (DSC) is proposed for inverted pendulum system. This scheme overcomes the problem of “explosion of complexity” which is inherent in the traditional backstepping technique. Meanwhile, the effect of input saturation constrains is considered in the control design. All the signals in the closed-loop system are proved uniformly ultimately bounded. Finally, the experimental platform simulation results are used to demonstrate the effectiveness of the proposed scheme.


Inverted pendulum system Neural network Dynamic surface control Input saturation 



This work is supported in part by the National Natural Science Foundation of China (Grant No. 51179019, 60874056), the Natural Science Foundation of Liaoning Province (Grant No. 20102012), the Program for Liaoning Excellent Talents in University (LNET) (Grant No. LR2012016), and the Fundamental Research Funds for the Central Universities (2011QN097).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Enping Wei
    • 1
  • Tieshan Li
    • 1
  • Junfang Li
    • 1
  • Yancai Hu
    • 1
  • Qiang Li
    • 1
  1. 1.Navigaion CollegeDalian Maritime UniversityDalianChina

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