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Design, analysis, and stiffness optimization of a three degree of freedom parallel manipulator

Published online by Cambridge University Press:  05 May 2009

Zhen Gao,
Dan Zhang,
Xiaolin Hu and
Yunjian Ge
Zhen Gao
Affiliation:
Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui Province 230031, P. R. ChinaDepartment of Automation, University of Science and Technology of China, Hefei, Anhui Province 230027, P. R. China
Dan Zhang*
Affiliation:
Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Ontario, CanadaL1H 7K4
Xiaolin Hu
Affiliation:
Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Ontario, CanadaL1H 7K4
Yunjian Ge
Affiliation:
Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui Province 230031, P. R. China
*
*Corresponding author. E-mail: dan.zhang@uoit.ca
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Summary

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This paper proposed a novel three degree of freedom (DOF) parallel manipulator—two translations and one rotation. The mobility study and inverse kinematic analysis are conducted, and a CAD model is presented showing the design features. The optimization techniques based on artificial intelligence approaches are investigated to improve the system stiffness of the proposed 3-DOF parallel manipulator. Genetic algorithms and artificial neural networks are implemented as the intelligent optimization methods for the stiffness synthesis. The mean value and the standard deviation of the global stiffness distribution are proposed as the design indices. Both the single objective and multi-objective optimization issues are addressed. The effectiveness of this methodology is validated with Matlab.

Keywords

Parallel manipulatorStiffness optimizationArtificial intelligence approachesdegree of freedomParallelogram structure

Information

Type
Article
Information
Robotica , Volume 28 , Issue 3 , May 2010, pp. 349 - 357
Copyright
Copyright © Cambridge University Press 2009

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