Skip to main content

A Neuro-genetic Control Scheme Application for Industrial R 3 Workspaces

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6076))

Abstract

This work presents a neuro-genetic control scheme for a R 3 workspace application. The solution is based on a Multi Objective Genetic Algorithm reference generator and an Adaptive Predictive Neural Network Controller. Crane position control is presented as an application of the proposed control scheme.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anand, V.B.: Computer Graphics and Geometric Modeling for Engineers. John Wiley & Sons, Inc., New York (1993)

    Google Scholar 

  2. Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Heidelberg (2003)

    Book  MATH  Google Scholar 

  3. Fujinaka, T., Kishida, Y., Yoshioka, M., Omatu, S.: Stabilization of double inverted pendulum with self-tuning neuro-pid. IJCNN 4, 345–348 (2000)

    Google Scholar 

  4. Galvan, J.B.: Tuning of optimal neural controllers. In: Proc. Int. Conf. on Engineering of Intelligent Systems, pp. 213–219 (1998)

    Google Scholar 

  5. Graña, M., Torrealdea, F.J.: Hierarchically structured systems. European Journal of Operational Research 25, 20–26 (1986)

    Article  Google Scholar 

  6. Hagan, M.T., Menhaj, M.B.: Training feedforward networks with the marquardt algorithm. IEEE Transactions on Neural Networks 5(6), 989–993 (1994)

    Article  Google Scholar 

  7. Hornik, K., Stinchcombe, M., White, H.: Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks. Neural Networks 3, 551–560 (1990)

    Article  Google Scholar 

  8. Irigoyen, E., Galvan, J.B., Perez-Ilzarbe, M.J.: Neural networks for constrained optimal control of nonlinear systems. IJCNN 4, 299–304 (2000)

    Google Scholar 

  9. Irigoyen, E., Galvn, J.B., Prez-Ilzarbe, M.J.: A neuro predictive controller for constrained nonlinear systems. In: IASTED International Conference Artificial Intelligence and Applications (2003)

    Google Scholar 

  10. Lu, C.-H., Tsai, C.-C.: Adaptive predictive control with recurrent neural network for industrial processes: An application to temperature control of a variable-frequency oil-cooling machine. IEEE Transactions on Industrial Electronics 55(3), 1366–1375 (2008)

    Article  Google Scholar 

  11. Pauluk, M., Korytowski, A., Turnau, A., Szymkat, M.: Time optimal control of 3d crane. In: Proceedings of the 7th Inter. Conference on Methods and Models in Automation and Robotics, pp. 927–936 (2001)

    Google Scholar 

  12. Suh, J.-H., Lee, J.-W., Lee, Y.-J., Lee, K.-S.: An automatic travel control of a container crane using neural network predictive pid control technique. International Journal of Precision Engineering and Manufacturing 7(1), 35–41 (2006)

    Google Scholar 

  13. Tan, K.K., Lee, T.H., Huang, S.N., Leu, F.M.: Adaptive-predictive control of a class of siso nonlinear systems. Dynamics and Control 11(2), 151–174 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  14. Valera, J., Irigoyen, E., Gomez-Garay, V., Artaza, F.: Application of neuro-genetic techniques in solving industrial crane kinematic control problem. In: IEEE International Conference on Mechatronics, pp. 231–237 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Irigoyen, E., Larrea, M., Valera, J., Gómez, V., Artaza, F. (2010). A Neuro-genetic Control Scheme Application for Industrial R 3 Workspaces. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-13769-3_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13768-6

  • Online ISBN: 978-3-642-13769-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics