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Journal of Applied Sciences

Year: 2013 | Volume: 13 | Issue: 14 | Page No.: 2819-2824
DOI: 10.3923/jas.2013.2819.2824
Robot Dynamic Identification Based on the Immune Clonal Selection Algorithm
Liu Haitao and Zhang Tie

Abstract: This study deals with the dynamic modeling and excitation trajectory optimization of the RB industrial robot. In the identification, the 6-DOF robot is simplified as the first 3-DOF dynamic model to get the complete dynamic expression and reduced observation matrix and an immune clonal selection algorithm is present to obtain the optimal excitation trajectory to improve the accuracy of dynamic parameters. Simulations show that this optimization algorithm is effective and the accuracy of the estimated parameters directly depends on the selection of excitation trajectory.

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How to cite this article
Liu Haitao and Zhang Tie, 2013. Robot Dynamic Identification Based on the Immune Clonal Selection Algorithm. Journal of Applied Sciences, 13: 2819-2824.

Keywords: Robot, dynamic identification and immune clonal selection algorithm

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