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This paper proposed a model predictive control (MPC) algorithm based on differential flatness for trajectory tracking of 3-degree-of-freedom (3-DOF) cable driven parallel robots (CDPRs). The configuration and modeling of the 3-DOF CDPR is presented. The nonlinear dynamic model of the CDPR system is transformed into a linear system using the differential flatness property. This transformation provides the foundation for subsequent controller design. Then an MPC algorithm is developed for the linearized CDPR dynamic model, explicitly incorporating tension constraints to ensure feasible and reliable control. The performance of the proposed control algorithm is validated through numerical simulations conducted in two scenarios. The first scenario evaluates the robot’s ability to reach a specified point, while the second examines its capability to track a helical trajectory. The simulation results demonstrate that the designed control algorithm enables the CDPR to effectively follow the desired trajectories.

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Model Predictive Controller for 3-DOF Cable Driven Parallel Robots Trajectory Tracking Based on Differential Flatness

  • 会议论文

  • 发表日期：

    2025年

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  • Zhenping Wu,
  • Yuyang Lin,
  • Zhongshen Li,
  • Tianliang Lin,
  • Yaqing Zheng

摘要

This paper proposed a model predictive control (MPC) algorithm based on differential flatness for trajectory tracking of 3-degree-of-freedom (3-DOF) cable driven parallel robots (CDPRs). The configuration and modeling of the 3-DOF CDPR is presented. The nonlinear dynamic model of the CDPR system is transformed into a linear system using the differential flatness property. This transformation provides the foundation for subsequent controller design. Then an MPC algorithm is developed for the linearized CDPR dynamic model, explicitly incorporating tension constraints to ensure feasible and reliable control. The performance of the proposed control algorithm is validated through numerical simulations conducted in two scenarios. The first scenario evaluates the robot’s ability to reach a specified point, while the second examines its capability to track a helical trajectory. The simulation results demonstrate that the designed control algorithm enables the CDPR to effectively follow the desired trajectories.