Abstract
Based on genetic algorithms, this paper presents a two-step offline method for the parameter identification of LuGre friction model. In the first step, four static parameters are estimated through the Stribeck curve, and in the second step, two dynamic parameters are obtained by the limit cycle output of the system. Genetic algorithms are used in both steps to minimize the identification errors. At last, the simulation results have shown the effectiveness of the proposed method for friction parameter identification.
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