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Proceedings Paper

Application of particle swarm optimization in model updating for wire-driven parallel manipulators
Author(s): Suilu Yue; Liaoni Wu; Yifeng Chen; Qi Lin
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Paper Abstract

In the wire-driven parallel suspension system, because manufacturing and assembling deviations exist, the expected control accuracy can not be reached. A mathematical model of wire-driven parallel manipulators is established. Effects of the deviations eliminated can improve the accuracy of the mathematical model. Particle swarm optimization (PSO) is a robust stochastic evolutionary computation technique, which is very easy to understand and implement. Particle swarm optimization is used to calculate model deviations and find values of the deviations. The results obtained by the particle swarm optimization algorithm can update the mathematical model of the wire-driven parallel manipulators and improve the control accuracy of the wire-driven suspension system.

Paper Details

Date Published: 13 March 2013
PDF: 4 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 878420 (13 March 2013); doi: 10.1117/12.2014354
Show Author Affiliations
Suilu Yue, Xiamen Univ. (China)
Liaoni Wu, Xiamen Univ. (China)
Yifeng Chen, Xiamen Univ. (China)
Qi Lin, Xiamen Univ. (China)


Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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