Volume 36 Issue 3
Jun.  2022
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Article Navigation >  Journal of Shanghai University of Engineering Science  > 2022  >  36(3): 261-266
SONG Jiqiang, ZHANG Aihua, YANG Lingyao. Trajectory tracking control of micro positioning platform based on dynamic sliding mode[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 261-266. doi: 10.12299/jsues.21-0193
Citation: SONG Jiqiang, ZHANG Aihua, YANG Lingyao. Trajectory tracking control of micro positioning platform based on dynamic sliding mode[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 261-266. doi: 10.12299/jsues.21-0193
shu

Trajectory tracking control of micro positioning platform based on dynamic sliding mode

doi: 10.12299/jsues.21-0193

  • School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

  • Received Date: 2021-09-22
  • Publish Date: 2022-06-30
    Abstract

  • As a high-precision motion platform, the micro positioning platform driven by the voice coil motor is widely used in precision machining, micro-electromechanical and other fields. Aiming at the high-precision and stable tracking control problem of the micro positioning platform driven by the voice coil motor, combining normalization method with theoretical modeling parameters, a mathematical model of second-order differential equation with parameter uncertainties was established, and the actual displacement of the flexible mechanism was taken as input and the platform control rate was taken as output. In view of the uncertain characteristics of the model parameters, the second-order sliding mode surface of the error was established to propose tracking control of micro positioning platform based on dynamic sliding mode, and the conclusion of system stability through Lyapunov's stability theory was obtained. The proposed control algorithm was analyzed by platform test comparison, the results show that the proposed dynamic sliding mode control algorithm can complete the trajectory tracking with less chatter. The tracking accuracy of the algorithm has improved by 13.4% and 4% compared to traditional sliding mode control, which has a smoother tracking and a good engineering prospects.

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