Adaptive Wavelet Neural Network Friction Compensation of Mechanical Systems

  • Shen-min Song
  • Zhuo-yi Song
  • Xing-lin Chen
  • Guangren Duan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


Recently, based on multi-resolution analysis, wavelet neural networks (WNN) have been proposed as an alternative to NN for approximating arbitrary nonlinear functions in L 2(R). Discontinuous friction function is an unavoidable nonlinear effect that can limit control performance in mechanical systems. In this paper, adaptive WNN is used to design a friction compensator for a single joint mechanical system. Then asymptotically stability of the system is assured by adding a PD controller and adaptive robust terms. The simulation results show the validity of the control scheme.


Tracking Error Wavelet Neural Network Neural Network Control Friction Compensation Friction Function 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shen-min Song
    • 1
  • Zhuo-yi Song
    • 1
  • Xing-lin Chen
    • 1
  • Guangren Duan
    • 1
  1. 1.School of Astronautics, Department of Control Science and EngineeringHarbin Institute of TechnologyHarbinChina

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