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Error analysis and optimal design of a class of translational parallel kinematic machine using particle swarm optimization

Published online by Cambridge University Press:  01 January 2009

Qingsong Xu
Affiliation:
Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Av. Padre Tomás Pereira, Taipa, Macao SAR, P.R. China
Yangmin Li*
Affiliation:
Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Av. Padre Tomás Pereira, Taipa, Macao SAR, P.R. China
*
*Corresponding author. E-mail: ymli@umac.mo

Summary

In this paper, the optimization of architectural parameters for a class of translational parallel kinematic machine (PKM) is performed with the particle swarm optimization (PSO) to achieve the best accuracy characteristics. The conventional error transformation matrix (ETM) is derived based on the differentiation of kinematic equations, and a new error amplification index (EAI) over a usable workspace is proposed as an error performance index for the optimization. To validate the efficiency of the PSO method, both the traditional direct search method and the genetic algorithm (GA) are implemented as well. The simulation results not only show the advantages of PSO method for the architectural optimization, but also reveal the necessity to introduce the EAI for the optimal design. And the results are valuable for architectural design of the PKM for machine tool applications.

Type
Article
Copyright
Copyright © Cambridge University Press 2008

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