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Published in:
2010 | OriginalPaper | Chapter
Optimum Motion Control for Stacking Robot
Authors : Xiaoming Zhang, Nan Luan, Zhong Dong, Liming Chen
Published in: Advances in Neural Network Research and Applications
Publisher: Springer Berlin Heidelberg
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Stacking speed is an important parameter to estimate the capacities of robotic system. In this paper, an innovative method based on ILC (Iterative Learning Control) could be used to optimize the speed of the industrial robots. By learning following error, the robotic system could reach the optimum speed within the permissible error range and achieve the optimization of the stacking robotic system. Furthermore, requiring little to model the robotic system, ILC is easy to be realized in practice. The results of the system simulation indicate, under the circumstances of computing robotic system parameter and comparing the optimization with ILC to the original results, that ILC could increase the stacking speed a lot through improving local speed.