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Identification of Dynamic Parameters in a DC Motor Using Step and Ramp Torque Response Methods.

Jorge Antonio Cardona Soto1, Israel U Ponce2, Israel Soto2

  • 1Universidad Tecnológica de Chihuahua, Chihuahua, CP 3126, Mexico.

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Summary
This summary is machine-generated.

This study introduces two analytical methods for identifying DC motor dynamic parameters like inertia and friction, crucial for precise motion control in robotics. The validated methods offer practical, computationally inexpensive solutions for enhancing robotic system performance.

Keywords:
Coulomb frictionDC motorparameter estimationparameter identificationviscous friction

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Area of Science:

  • Robotics and Mechatronics
  • Control Systems Engineering
  • Mechanical Engineering

Background:

  • DC motors are essential for motion in manufacturing and robotics.
  • Precise control of speed and position is critical for these applications.
  • Accurate estimation of dynamic parameters (inertia, friction) is needed for efficient control strategies.

Purpose of the Study:

  • To present two analytical methodologies for DC motor parameter identification.
  • To enable practical and computationally inexpensive estimation of inertia and friction.
  • To validate the identified parameters for improving motor control.

Main Methods:

  • Analysis of angular position data from a DC motor under constant torque (step) and ramp excitation.
  • Development of entirely analytical procedures based on system response to inputs.
  • Utilization of a hardware-in-loop (HIL) system for real-time data acquisition and processing in MATLAB/Simulink.

Main Results:

  • Accurate and consistent identification of DC motor inertia and friction parameters.
  • Validation of the identified parameters through implementation of a closed-loop proportional-integral (PI) speed control system.
  • Demonstration of the practical applicability of the analytical methods.

Conclusions:

  • The proposed analytical methods effectively identify DC motor dynamic parameters.
  • The validated parameters are crucial for designing efficient and sustainable control strategies.
  • These methods enhance motor control performance in diverse robotic applications.