Advertisement

An Adaptive Controller Using Wavelet Network for Five-Bar Manipulators with Deadzone Inputs

  • Tien Dung Le
  • Hee-Jun Kang
Part of the Communications in Computer and Information Science book series (CCIS, volume 375)

Abstract

In this paper, an adaptive model-based control scheme is proposed for tracking control of five-bar manipulators with deadzone inputs. The proposed controller is based on the combination of nominal dynamic model of the five-bar manipulator, a wavelet network and a deadzone precompensator. The wavelet network and the precompensator are used for compensating the unknown deadzone inputs, modeling errors and uncertainties of the five-bar manipulator. The adaptation laws are derived for tuning parameters of the precompensator and wavelet network. The efficiency of the proposed control scheme is verified by comparative simulations.

Keywords

Wavelet Network Adaptive Controller Model-based Control Deadzone Input Five-bar Manipulator 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alexandridis, A.K., Zapranis, A.D.: Wavelet neural networks: A practical guide. Neural Networks 42, 1–27 (2013)CrossRefGoogle Scholar
  2. 2.
    Cao, J., Lin, Z., Huang, G.-B.: Composite function wavelet neural networks with extreme learning machine. Neurocomputing 73(7-9), 1405–1416 (2010)CrossRefGoogle Scholar
  3. 3.
    Zhang, Q., Benveniste, A.: Wavelet networks. IEEE Transactions on Neural Networks 3(6), 889–898 (1992)CrossRefGoogle Scholar
  4. 4.
    Lewis, F.L., et al.: Deadzone compensation in motion control systems using adaptive fuzzy logic control. IEEE Transactions on Control Systems Technology 7(6), 731–742 (1999)CrossRefGoogle Scholar
  5. 5.
    Selmic, R.R., Lewis, F.L.: Deadzone compensation in motion control systems using neural networks. IEEE Transactions on Automatic Control 45(4), 602–613 (2000)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Chuxiong, H., Bin, Y., Qingfeng, W.: Performance-Oriented Adaptive Robust Control of a Class of Nonlinear Systems Preceded by Unknown Dead Zone With Comparative Experimental Results. IEEE/ASME Transactions on Mechatronics 18(1) (2013)Google Scholar
  7. 7.
    Chuxiong, H., Bin, Y., Qingfeng, W.: Adaptive Robust Precision Motion Control of Systems With Unknown Input Dead-Zones: A Case Study With Comparative Experiments. IEEE Transactions on Industrial Electronics 58(6), 2454–2464 (2011)CrossRefGoogle Scholar
  8. 8.
    Wang, X.-S., Su, C.-Y., Hong, H.: Robust adaptive control of a class of nonlinear systems with unknown dead-zone. Automatica 40(3), 407–413 (2004)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Chiang, C.-C.: Adaptive Fuzzy Tracking Control for Uncertain Nonlinear Time-Delay Systems with Unknown Dead-Zone Input. Mathematical Problems in Engineering (2013)Google Scholar
  10. 10.
    Shaocheng, T., Yongming, L.: Adaptive Fuzzy Output Feedback Control of MIMO Nonlinear Systems With Unknown Dead-Zone Inputs. IEEE Transactions on Fuzzy Systems 21(1), 134–146 (2013)CrossRefGoogle Scholar
  11. 11.
    Le, T.D., et al.: An online self-gain tuning method using neural networks for nonlinear PD computed torque controller of a 2-dof parallel manipulator. Neurocomputing (2012)Google Scholar
  12. 12.
    Le, T.D., Kang, H.-J., Suh, Y.-S.: Chattering-Free Neuro-Sliding Mode Control of 2-DOF Planar Parallel Manipulators. Internation Journal of Advanced Robotic Systems (October 22, 2013) Google Scholar
  13. 13.
    Lin, C.K.: Adaptive tracking controller design for robotic systems using Gaussian wavelet networks. IEE Proceedings Control Theory and Applications 149(4), 316–322 (2002)CrossRefGoogle Scholar
  14. 14.
    Le Tien, D., Hee-Jun, K., Young-Shick, R.: Robot manipulator modeling in Matlab-SimMechanics with PD control and online gravity compensation. In: 2010 International Forum on Strategic Technology, IFOST (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tien Dung Le
    • 1
  • Hee-Jun Kang
    • 2
  1. 1.Graduate School of Electrical EngineeringUniversity of UlsanUlsanSouth Korea
  2. 2.School of Electrical EngineeringUniversity of UlsanUlsanSouth Korea

Personalised recommendations