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

Qingsong Xu, Yangmin Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

49 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)67-78
Number of pages12
Issue number1
Publication statusPublished - 1 Jan 2009
Externally publishedYes


  • Accuracy
  • Error model
  • Optimal design
  • Parallel manipulators
  • Workspace

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications

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