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Operation of the Collaborative Composite Manufacturing CCM System
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QPSO-MPC based tracking algorithm for cable-driven continuum robots.

Qi Chen1, Yanan Qin1, Gelun Li2

  • 1School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China.

Frontiers in Neurorobotics
|October 31, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a Quantum Particle Swarm Optimization-Model Predictive Control (QPSO-MPC) for cable-driven continuum robots (CDCRs). The QPSO-MPC algorithm significantly enhances trajectory tracking precision and control stability in confined spaces.

Keywords:
MPCQPSOcable-driven continuum robotscontrol stabilitytrajectory tracking precision

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Optimization Algorithms

Background:

  • Cable-driven continuum robots (CDCRs) offer high flexibility for navigating confined spaces.
  • Designing effective trajectory tracking for CDCRs is challenging due to nonlinear dynamics and cable hysteresis.
  • Existing control methods may struggle with the complex behaviors of CDCRs.

Purpose of the Study:

  • To develop an advanced trajectory tracking algorithm for CDCRs.
  • To improve control stability and precision in complex robotic tasks.
  • To address the limitations of conventional control methods in CDCR applications.

Main Methods:

  • Kinematic analysis of CDCRs using piecewise constant curvature and homogeneous coordinate transformation.
  • Development of a Model Predictive Control (MPC) algorithm.
  • Integration of Quantum Particle Swarm Optimization (QPSO) into the MPC's rolling optimization process.
  • Simulation and experimental validation of the proposed QPSO-MPC algorithm.

Main Results:

  • The QPSO-MPC algorithm demonstrated superior global optimization, robustness, and fast convergence.
  • High control stability and trajectory tracking precision were achieved in both simulations and experiments.
  • Tracking error was reduced by at least 43% compared to standard MPC and 24% compared to PSO-based MPC.

Conclusions:

  • The QPSO-MPC is an effective solution for precise trajectory tracking in CDCRs.
  • The proposed method overcomes limitations associated with nonlinear dynamics and cable hysteresis.
  • This advancement enables more reliable performance of CDCRs in complex, constrained environments.