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

  • Ramon Garcia-Hernandez
  • Edgar N. Sanchez
  • Miguel A. Llama
  • Jose A. Ruz-Hernandez
Part of the Studies in Computational Intelligence book series (SCI, volume 465)


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.


Decentralized control High-order neural networks Extended Kalman filter Backstepping Industrial robot 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ramon Garcia-Hernandez
    • 1
  • Edgar N. Sanchez
    • 2
  • Miguel A. Llama
    • 3
  • Jose A. Ruz-Hernandez
    • 1
  1. 1.Facultad de IngenieriaUniversidad Autonoma del CarmenCd. del CarmenMexico
  2. 2.Department of Electrical EngineeringCINVESTAV Unidad GuadalajaraCol. El Bajío, ZapopanMexico
  3. 3.Division de Estudios de Posgrado e InvestigacionInstituto Tecnologico de la LagunaTorreonMexico

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