Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77869
Title: Nonlinear friction and dynamical identification for a robot manipulator with improved cuckoo search algorithm
Authors: Ding, L 
Li, X
Li, Q
Chao, Y
Issue Date: 2018
Publisher: Hindawi
Source: Journal of robotics, 2018, v. 2018, 8219123, p. 1-10 How to cite?
Journal: Journal of robotics 
Abstract: This paper concerns the problem of dynamical identification for an industrial robot manipulator and presents an identification procedure based on an improved cuckoo search algorithm. Firstly, a dynamical model of a 6-DOF industrial serial robot has been derived. And a nonlinear friction model is added to describe the friction characteristic at motion reversal. Secondly, we use a cuckoo search algorithm to identify the unknown parameters. To enhance the performance of the original algorithm, both chaotic operator and emotion operator are employed to help the algorithm jump out of local optimum. Then, the proposed algorithm has been implemented on the first three joints of the ER-16 robot manipulator through an identification experiment. The results show that (1) the proposed algorithm has higher identification accuracy over the cuckoo search algorithm or particle swarm optimization algorithm and (2) compared to linear friction model the nonlinear model can describe the friction characteristic of joints better.
URI: http://hdl.handle.net/10397/77869
ISSN: 1687-9600
EISSN: 1687-9619
DOI: 10.1155/2018/8219123
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