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  • 标题:Predefined-time convergence in task-based inverse dynamics using time base generators
  • 本地全文:下载
  • 作者:Gustavo Arechavaleta ; Jonathan Obregón ; Héctor M. Becerra
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:13
  • 页码:443-449
  • DOI:10.1016/j.ifacol.2018.07.318
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, we propose a state-feedback controller that is capable to achieve predefined-time convergence for a class of nonlinear second order systems that can be linearized to a perturbed double integrator. The controller relies on the use of time base generators. Also, we study the link between the proposed predefined-time controller and the widely applied task-based inverse dynamics framework to control kinematically redundant robots. We show that positioning tasks assigned to the robot subject to joint-limits constraints are successfully completed in a user defined time regardless of the robot’s initial state. Moreover, the proposed task-based controller is robust to parametric uncertainties and matched disturbances since it includes a term given by a super-twisting control. This is verified through simulations with a kinematically redundant mobile-manipulator KUKA youBot with eight degrees of freedom.
  • 关键词:Keywordspredefined-time convergencerobot control in task spaceinverse dynamics
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