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Dynamic modeling and performance analysis of a lower-mobility parallel robot with a rotatable platform.

Zhen Liu1, Song Yang1, Tao Ding1

  • 1Xi'an Research Inst. of Hi-Tech, Xi'an 710025, China.

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Summary

Redundant drives significantly reduce elastic deformation and vibration in high-speed parallel robots. This leads to superior dynamic performance, improved motion accuracy, and better overall system efficiency compared to non-redundant drives.

Keywords:
assumed mode methodparallel robotredundant actuationrigid-flexible coupling dynamic modeling

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Area of Science:

  • Robotics
  • Mechanical Engineering
  • Dynamics and Control

Background:

  • High-speed, lightweight parallel robots are increasingly utilized.
  • Elastic deformation significantly impacts robot dynamic performance during operation.

Purpose of the Study:

  • To design and investigate a 3 Degrees of Freedom (DOF) parallel robot with a rotatable working platform.
  • To develop a rigid-flexible coupled dynamics model for analyzing elastic deformation effects.

Main Methods:

  • Developed a rigid-flexible coupled dynamics model using the Assumed Mode Method and Augmented Lagrange Method.
  • Incorporated a fully flexible rod and a rigid platform.
  • Utilized numerical simulations with driving moments under three different modes as feedforward control.

Main Results:

  • Redundant drive configurations resulted in significantly smaller elastic deformation of the flexible rod compared to non-redundant drives.
  • Redundant drives demonstrated a superior vibration suppression effect.
  • The system's dynamic performance, motion accuracy, and driving mode 'b' were found to be superior under redundant drive conditions.

Conclusions:

  • The rigid-flexible coupled dynamics model accurately represents the behavior of parallel robots with elastic components.
  • Redundant drive strategies are effective in mitigating elastic deformation and enhancing the dynamic performance of parallel robots.
  • The findings provide valuable insights for designing and controlling high-performance parallel robotic systems.