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Collaborative Control for a Robot Manipulator via Interaction-Force-Based Impedance Method and Extremum Seeking

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Summary
This summary is machine-generated.

This study presents an adaptive impedance control for robotic manipulators using extremum seeking. It streamlines contact impedance adjustment by optimizing parameters in real-time, enhancing robotic control performance.

Keywords:
adaptive impedance controlextremum seeking methodrobot manipulator

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Area of Science:

  • Robotics
  • Control Systems
  • Mechatronics

Background:

  • Robotic manipulators require precise control for tasks involving physical interaction.
  • Traditional impedance control methods often rely on torque sensors and struggle with uncertainties.
  • Adaptive control strategies are needed to enhance robustness and performance in dynamic environments.

Purpose of the Study:

  • To introduce a novel adaptive impedance control strategy for robotic manipulators.
  • To eliminate the need for torque sensors by employing a disturbance observer.
  • To enable real-time, online optimization of control parameters for various tasks.

Main Methods:

  • Utilized extremum seeking technique for adaptive parameter optimization.
  • Implemented a model-based disturbance observer (DOB) for contact force estimation.
  • Developed an impedance vector to compensate for motor uncertainties and unknown couplings.
  • Incorporated joint tracking errors and contact force fluctuations into a cost function.

Main Results:

  • The proposed controller successfully estimated contact forces without torque sensors.
  • Adaptive optimization of control parameters was achieved in real-time via extremum seeking.
  • The controller demonstrated a streamlined design for adjusting manipulator contact impedance.
  • Experimental results validated the online tuning capability based on cost function variations.

Conclusions:

  • The adaptive impedance control strategy offers a more efficient and robust approach to robotic manipulation.
  • Extremum seeking provides an effective mechanism for online tuning of control parameters.
  • The method enhances manipulator performance in tasks requiring precise contact force control.