Multi-objective performance optimization of a parallel robotic machine tool

Dan Zhang, Zhen Gao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

This research is investigated on the multi-objective performance optimization of a parallel robotic machine tool which is expected to be applied as a next generation of computer numerical control (CNC) machine. The system configuration and the kinematic model are detailed introduced. The performance maps including dexterity and workspace are generated and illustrated. The multi-objective optimal performance indices are investigated based on the integration of the evolutionary algorithm and Pareto frontier sets. The developed technologies and approaches are generic and also feasible for the design, modeling and improvement of other parallel kinematic machines.

Original languageEnglish
Title of host publicationProceedings of 2012 8th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2012
Pages154-159
Number of pages6
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 8th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2012 - Suzhou, China
Duration: 8 Jul 201210 Jul 2012

Publication series

NameProceedings of 2012 8th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2012

Conference

Conference2012 8th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2012
Country/TerritoryChina
CitySuzhou
Period8/07/1210/07/12

Keywords

  • dexterity
  • evolutionary algorithm
  • multi-objective performance optimization
  • Parallel robotic machine tool
  • workspace

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering

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