Multi-objective optimization of a typical parallel tracking mechanism considering parameter uncertainty is carried out in this paper. Both dimensional and sectional parameters are regarded as design variables. Workspace, kinematic, stiffness, and dynamic performances are simultaneously considered in formulating optimal objectives and constraint conditions. Considering manufacturing and assembling errors, parameter uncertainty is modeled and evaluated to minimize their effects on the optimized performances. Analytical models between objectives and design variables are established to improve the efficiency of optimization while its accuracy is assured. The study of parameter uncertainty and analytical mapping model is incorporated in the optimization of the parallel tracking mechanism. With the aid of particle swarm algorithm, a cluster of solutions, called Pareto frontier, are obtained. By proposing an index, a cooperative equilibrium point representing the balance among objectives is selected and the optimized parameters are determined. The present study is expected to help designers build optimized parallel tracking mechanism in an effective and efficient manner.
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August 2018
Research-Article
Multi-Objective Optimization of Parallel Tracking Mechanism Considering Parameter Uncertainty
Yang Qi,
Yang Qi
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: qiyang@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: qiyang@tju.edu.cn
Search for other works by this author on:
Tao Sun,
Tao Sun
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: stao@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: stao@tju.edu.cn
Search for other works by this author on:
Yimin Song
Yimin Song
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: ymsong@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: ymsong@tju.edu.cn
Search for other works by this author on:
Yang Qi
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: qiyang@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: qiyang@tju.edu.cn
Tao Sun
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: stao@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: stao@tju.edu.cn
Yimin Song
Key Laboratory of Mechanism,
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: ymsong@tju.edu.cn
Theory and Equipment Design of
Ministry of Education,
Tianjin University,
Tianjin 300350, China
e-mail: ymsong@tju.edu.cn
1Corresponding author.
Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received June 23, 2017; final manuscript received March 9, 2018; published online April 18, 2018. Assoc. Editor: Clement Gosselin.
J. Mechanisms Robotics. Aug 2018, 10(4): 041006 (12 pages)
Published Online: April 18, 2018
Article history
Received:
June 23, 2017
Revised:
March 9, 2018
Citation
Qi, Y., Sun, T., and Song, Y. (April 18, 2018). "Multi-Objective Optimization of Parallel Tracking Mechanism Considering Parameter Uncertainty." ASME. J. Mechanisms Robotics. August 2018; 10(4): 041006. https://doi.org/10.1115/1.4039771
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