13 March 2013 Application of particle swarm optimization in model updating for wire-driven parallel manipulators
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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.
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Suilu Yue, Liaoni Wu, Yifeng Chen, Qi Lin, "Application of particle swarm optimization in model updating for wire-driven parallel manipulators", 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; https://doi.org/10.1117/12.2014354
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