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Related Experiment Video

Updated: Jun 13, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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An improve nonlinear robust control approach for robotic manipulators with PSO-based global optimization strategy.

Peihao Yue1,2, Bowen Xu3, Min Zhang2

  • 1College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.

Scientific Reports
|September 13, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a nonlinear active disturbance rejection control (NADRC) strategy for robotic manipulators, enhancing trajectory tracking by addressing uncertainties and disturbances. An improved particle swarm optimization (IPSO) algorithm further boosts control accuracy.

Keywords:
Active disturbance rejection controllerNonlinear controlNonlinear dynamicsParticle swarm optimizationRobotic manipulator

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Artificial Intelligence

Background:

  • Robotic manipulator trajectory tracking is challenged by factors like dead zones, saturation, and uncertain dynamics.
  • These challenges increase the complexity of modeling and control, hindering precise robotic movements.
  • Existing control strategies often struggle to robustly handle these real-world complexities.

Purpose of the Study:

  • To propose a novel nonlinear active disturbance rejection control (NADRC) strategy for robotic manipulators.
  • To enhance the robustness and accuracy of trajectory tracking in the presence of uncertainties and disturbances.
  • To optimize the NADRC controller parameters for improved performance.

Main Methods:

  • A nonlinear active disturbance rejection control (NADRC) strategy was developed for robotic manipulators.
  • An extended state observer was integrated to estimate and compensate for model uncertainties and external disturbances.
  • An improved particle swarm optimization (IPSO) algorithm, incorporating chaos theory, was designed for controller parameter tuning.

Main Results:

  • The proposed NADRC strategy demonstrated robust trajectory tracking capabilities for robotic manipulators.
  • The extended state observer effectively observed and compensated for system uncertainties and disturbances.
  • The IPSO algorithm significantly improved the tracking accuracy of the NADRC controller compared to standard methods.

Conclusions:

  • The developed NADRC strategy offers an effective solution for precise robotic manipulator trajectory tracking.
  • The integration of an extended state observer and IPSO optimization enhances control robustness and accuracy.
  • Comparative studies validate the superiority of the proposed control strategy over conventional methods.