This paper concerns the problem of dynamical identification for an industrial robot manipulator and presents an identification\nprocedure based on an improved cuckoo search algorithm. Firstly, a dynamical model of a 6-DOF industrial serial robot has been\nderived. And a nonlinear friction model is added to describe the friction characteristic at motion reversal. Secondly, we use a\ncuckoo search algorithm to identify the unknown parameters. To enhance the performance of the original algorithm, both chaotic\noperator and emotion operator are employed to help the algorithm jump out of local optimum.Then, the proposed algorithm has\nbeen implemented on the first three joints of the ER-16 robot manipulator through an identification experiment. The results show\nthat (1) the proposed algorithm has higher identification accuracy over the cuckoo search algorithm or particle swarmoptimization\nalgorithm and (2) compared to linear friction model the nonlinear model can describe the friction characteristic of joints better.
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