Skip to main content
SpringerLink
Log in

Control of an Industrial PA10-7CE Redundant Robot Using a Decentralized Neural Approach

  • Conference paper
Computational Intelligence (IJCCI 2011)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 465))

Included in the following conference series:

  • 1051 Accesses

Abstract

This paper presents a discrete-time decentralized control strategy for trajectory tracking of a seven degrees of freedom (DOF) redundant robot. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The neural network learning is performed online using Kalman filtering. The motion of each joint is controlled independently using only local angular position and velocity measurements. The proposed controller is validated via simulations.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Sanchez, E.N., Ricalde, L.J.: Trajectory tracking via adaptive recurrent neural control with input saturation. In: Proc. of International Joint Conference on Neural Networks, Portland, Oregon, pp. 359–364 (2003)

    Google Scholar 

  2. Santibañez, V., Kelly, R., Llama, M.A.: A novel global asymptotic stable set-point fuzzy controller with bounded torques for robot manipulators. IEEE Transactions on Fuzzy Systems 13(3), 362–372 (2005)

    Article  Google Scholar 

  3. Huang, S., Tan, K.K., Lee, T.H.: Decentralized control design for large-scale systems with strong interconnections using neural networks. IEEE Transactions on Automatic Control 48(5), 805–810 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  4. Liu, M.: Decentralized control of robot manipulators: nonlinear and adaptive approaches. IEEE Transactions on Automatic Control 44(2), 357–363 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  5. Ni, M.L., Er, M.J.: Decentralized control of robot manipulators with coupling and uncertainties. In: Proc. of the American Control Conference, Chicago, Illinois, pp. 3326–3330 (2000)

    Google Scholar 

  6. Karakasoglu, A., Sudharsanan, S.I., Sundareshan, M.K.: Identification and decentralized adaptive control using dynamical neural networks with application to robotic manipulators. IEEE Transactions on Neural Networks 4(6), 919–930 (1993)

    Article  Google Scholar 

  7. Safaric, R., Rodic, J.: Decentralized neural-network sliding-mode robot controller. In: Proc. of 26th Annual Conference on the IEEE Industrial Electronics Society, Nagoya, Aichi, Japan, pp. 906–911 (2000)

    Google Scholar 

  8. Krstic, M., Kanellakopoulos, I., Kokotovic, P.: Nonlinear and Adaptive Control Design. John Wiley & Sons Inc., New York (1995)

    MATH  Google Scholar 

  9. Ge, S.S., Zhang, J., Lee, T.H.: Adaptive neural network control for a class of MIMO nonlinear systems with disturbances in discrete-time. IEEE Transactions on Systems, Man, and Cybernetics Part B 34(4), 1630–1645 (2004)

    Article  Google Scholar 

  10. Alanis, A.Y., Sanchez, E.N., Loukianov, A.G.: Discrete-Time Adaptive Backstepping Nonlinear Control via High-Order Neural Networks. IEEE Transactions on Neural Networks 18(4), 1185–1195 (2007)

    Article  Google Scholar 

  11. Rovithakis, G.A., Christodoulou, M.A.: Adaptive Control with Recurrent High-Order Neural Networks. Springer, London (2000)

    Book  Google Scholar 

  12. Song, Y., Grizzle, J.W.: The extended Kalman filter as local asymptotic observer for discrete-time nonlinear systems. Journal of Mathematical Systems, Estimation and Control 5(1), 59–78 (1995)

    MathSciNet  MATH  Google Scholar 

  13. Higuchi, M., Kawamura, T., Kaikogi, T., Murata, T., Kawaguchi, M.: Mitsubishi clean room robot. Mitsubishi Heavy Industries, Ltd., Tecnical Review (2003)

    Google Scholar 

  14. Jamisola, R.S., Maciejewski, A.A., Roberts, R.G.: Failure-tolerant path planning for the PA-10 robot operating amongst obstacles. In: Proceedings of IEEE International Conference on Robotics and Automation, New Orleans, LA, USA, pp. 4995–5000 (2004)

    Google Scholar 

  15. Kennedy, C.W., Desai, J.P.: Force feedback using vision. In: Proceedings of IEEE International Conference on Advanced Robotics, Coímbra, Portugal (2003)

    Google Scholar 

  16. Ramirez, C.: Dynamic modeling and torque-mode control of the Mitsubishi PA10-7CE robot. Master Dissertation, Instituto Tecnológico de la Laguna, Torreón, Coahuila, Mexico (2008) (in Spanish)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Facultad de Ingenieria, Universidad Autonoma del Carmen, Calle 56 No. 4, Col. Benito Juarez, C.P 24180, Cd. del Carmen, Campeche, Mexico

    Ramon Garcia-Hernandez & Jose A. Ruz-Hernandez

  2. Department of Electrical Engineering, CINVESTAV Unidad Guadalajara, Av. del Bosque 1145, C.P. 45019, Col. El Bajío, Zapopan, Jalisco, Mexico

    Edgar N. Sanchez

  3. Division de Estudios de Posgrado e Investigacion, Instituto Tecnologico de la Laguna, Blvd. Revolucion y Cuauhtemoc S/N, C.P. 27000, Torreon, Coahuila, Mexico

    Miguel A. Llama

Authors
  1. Ramon Garcia-Hernandez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edgar N. Sanchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Miguel A. Llama
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jose A. Ruz-Hernandez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ramon Garcia-Hernandez .

Editor information

Editors and Affiliations

  1. , Images, Signals and, University PARIS-EST Creteil (UPEC), Paris 12, 3956, France

    Kurosh Madani

  2. , Departamento de Engenharia Informatica, University of Coimbra, Polo II - Pinhal de Marrocos, Coimbra, 3030, Portugal

    António Dourado

  3. Systems and Robotics Institute, Evolutionary Systems and, Instituto Superior Tecnico IST, Av. Rovisco Pais, Lisboa, 1049-001, Portugal

    Agostinho Rosa

  4. INSTICC, Polytechnic Institute of Setúbal /, Setubal, 2910-595, Portugal

    Joaquim Filipe

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Garcia-Hernandez, R., Sanchez, E.N., Llama, M.A., Ruz-Hernandez, J.A. (2013). Control of an Industrial PA10-7CE Redundant Robot Using a Decentralized Neural Approach. In: Madani, K., Dourado, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2011. Studies in Computational Intelligence, vol 465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35638-4_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35638-4_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35637-7

  • Online ISBN: 978-3-642-35638-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation