Kinetic Parameters Identification of Double Pendulum Robot

Dan Yuanhong, Li Zushu

Abstract


The model structure of Double Pendulum Robot (DPR) has been built up with Lagrange equations. To reduce the difference between simulation control and real-time control, the kinetic parameters of Double pendulum robot (DPR) is accurately identified with proposed improved genetic algorithm (IGA) which integrated hybrid coding, hamming distance, orthogonal experiment, feedback mutation, and a specially designed fitness function. This improved genetic algorithm (IGA) overcome the shortcoming of traditional genetic algorithm, strengthen global and local searching capability, and get results more close to global optimal solution.  Finally, the optimal results (kinetic parameter values) are applied to model, and make a contrast experiment of zero input response between searched optimal kinetic parameters and real kinetic parameters of DPR.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2174


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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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