Computed Torque Control for Robotic Manipulator

Published:

Project Overview

This project focuses on the design and implementation of a Computed Torque Control (CTC) system for robotic manipulator arms. The work demonstrates advanced control techniques for achieving precise trajectory tracking and disturbance rejection in robotic systems.

Key Achievements

  • Developed a comprehensive Computed Torque Control system for manipulator arm
  • Implemented and validated controller in simulation environment
  • Achieved robust performance with excellent trajectory tracking
  • Demonstrated effective disturbance rejection capabilities

Control System Design

  • Controller Architecture:
    • Implemented feed-forward computed torque control
    • Integrated PD feedback control for error compensation
    • Developed dynamic model compensation techniques
    • Real-time trajectory tracking system
  • System Modeling:
    • Full dynamic model of robotic manipulator
    • Non-linear compensation techniques
    • Gravity and Coriolis force consideration
    • Friction modeling and compensation

Performance Analysis

  • Trajectory Tracking:
    • Minimized tracking errors in joint space
    • Smooth motion profiles
    • Stable performance across operating range
    • Robust against model uncertainties
  • Stability Analysis:
    • Lyapunov stability verification
    • Robustness against parameter variations
    • Error convergence analysis
    • Performance bounds evaluation

Technologies Used

  • MATLAB/Simulink for simulation and analysis
  • Robotic System Toolbox
  • Control System Design Tools
  • Numerical Optimization Techniques

Key Results

  • Achieved sub-millimeter positioning accuracy
  • Demonstrated robust performance under varying loads
  • Successfully compensated for non-linear dynamics
  • Verified stability across operational workspace

Technical Details

  • Control Law Implementation:
    • Non-linear dynamic compensation
    • PD control gain optimization
    • Real-time computational efficiency
    • Adaptive parameter tuning
  • Validation Methods:
    • Extensive simulation testing
    • Multiple trajectory scenarios
    • Disturbance response analysis
    • Parameter sensitivity studies

Project Resources