Multi-objective Optimization of planar 3PRR (prismatic-revolute-revolute) parallel mechanism using genetic algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes multi-objective optimization of planar 3PRR parallel kinematics mechanism which offers the advantages of lower degree of freedom parallel kinematics mechanisms. Workspace area, minimum eigenvalue across the workspace, and stiffness condition number across the workspace are chosen to be the objectives in the optimization in order to gain as large workspace area as possible while maintaining high stiffness in all directions under the defined kinematics constraints of the mechanism. The multi-objective optimization has been conducted by using multi-objective genetic algorithm. It is shown that the multi-objective optimization compromises the improvement of all objectives by providing non-dominated solutions. A decision maker can pick a preferred solution among those solutions.

Original languageBritish English
Title of host publication2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509009169
DOIs
StatePublished - 2 Jul 2016
Event59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 - Abu Dhabi, United Arab Emirates
Duration: 16 Oct 201619 Oct 2016

Publication series

NameMidwest Symposium on Circuits and Systems
Volume0
ISSN (Print)1548-3746

Conference

Conference59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period16/10/1619/10/16

Keywords

  • 3PRR
  • Genetic algorithm
  • Multiobjective optimization
  • Parallel kinematics mechanism

Fingerprint

Dive into the research topics of 'Multi-objective Optimization of planar 3PRR (prismatic-revolute-revolute) parallel mechanism using genetic algorithm'. Together they form a unique fingerprint.

Cite this