Nonlinear Friction Dynamic Modeling and Velocity Planning of Flexible Parallel Robot
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    Abstract:

    In order to realize control of robot in high speed and accuracy, Lagrange method was applied to deduce dynamic model and nonlinear friction force dynamic compensation model based on Hensens & Kostic theory. The single point positioning error was analyzed before and after compensation. A kind of S type velocity planning method was designed based on the constrain model of maximum speed and acceleration. Performance test in real time was implanted between T and S types velocity control algorithm about position and speed tracing. The experiment data indicated that the maximum position tracking error and speed tracking error of T type velocity planning were increased to 78.1μm and 11.4mm/s. But those of S type velocity planning were only 37.8μm and 3.72mm/s. Location accuracy of S type planning at two termination points reached 8.1μm and 8.9μm. The maximum speed difference of S type planning was 1.74mm/s which was much smaller than 6.88mm/s of T type velocity planning. High precision of position control especially termination-point location was ensured by S type velocity planning algorithm. Its peak velocity mutation was much smaller and velocity curve was also smoother compared with that of T type velocity control algorithm. It was demonstrated that speed tracing performance and stability of motion were improved greatly. The contradiction of T type velocity planning existed between high speed movement and high precision control was effectively relieved. So S type velocity planning was much easier to realize the control of robot in high speed and accuracy. In order to verify the correctness of the simulation analysis conclusions,position error of robot was tested by laser interferometer under continuous motion at different speeds. Simulation data was less than experiment data. The data error was about 100μm between simulation and actual measurement. But the conclusions were consistent with the experiment. The validity of the simulation analysis method was verified.

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History
  • Received:September 08,2016
  • Revised:
  • Adopted:
  • Online: May 10,2017
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