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Optimal Trajectory Tracking Control With a 5R Parallel Robot

[+] Author Affiliations
Gianmarc Coppola, Dan Zhang

University of Ontario Institute of Technology, Oshawa, ON, Canada

Paper No. DETC2011-47752, pp. 949-958; 10 pages
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 6: 35th Mechanisms and Robotics Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5483-9
  • Copyright © 2011 by ASME


This work examines the control characteristics of a 5R parallel robotic manipulator subjected to two control studies. Firstly, fundamental aspects of dynamics are presented. Then a brief review of Particle Swarm Optimization (PSO) and feedforward Neural Networks (NN) is undertaken. Subsequently, to tackle the challenging problem of controller parameter tuning for parallel robots in trajectory tracking scenarios, a multi objective optimization problem is formulated for automatic tuning using PSO. This offline method is comparatively evaluated to the Nelder-Mead (NM) sequential simplex optimization scheme. Several results are attained illustrating the strengths and weaknesses of this method for parallel robot control. Then, an adaptive NN model reference control scheme using PSO is proposed. This scheme is proposed as one possible way to take advantage of the strong properties of the PSO online. The scheme is tested and several observations are outlined.

Copyright © 2011 by ASME



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