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  • 标题:A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator
  • 本地全文:下载
  • 作者:C. West ; A. Montazeri ; S.D. Monk
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:12
  • 页码:1261-1266
  • DOI:10.1016/j.ifacol.2016.07.688
  • 语种:English
  • 出版社:Elsevier
  • 摘要:In this paper the problem of dynamic modeling and parameter estimation of a seven degree of freedom hydraulic manipulator is investigated. The numerical model is developed in Simulink using Sim Mechanic and Simscape toolboxes with unknown/uncertain parameters. The aim of this paper is to develop a mechanism that enables us to find a feasible set of parameters for the robot that is consistent with measurements of the input, output, and states of the system under noisy and unknown operating conditions. As the first step a genetic algorithm is developed to solve an output error system identification problem for a specific joint, i.e. joint 2, such that the parameters of the joint converge to the desired set of parameters within an acceptable accuracy. The results can be straightforwardly extended to all joints of the manipulator.
  • 关键词:Parameter estimationSystem identificationNonlinear modelGenetic algorithmMathematical modeling
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