Accurate Trajectory Control of Robotic Manipulators.

Abstract

This report presents a control scheme for accurate trajectory following with robotic manipulators. The method uses feedforward control using model-based torques for fast operation and gross compensation, and adaptive feedback control for correcting deviations from the desired trajectory under feedforward control. The adaptive controller eliminates trajectory-following errors in the least squares sense. The control scheme takes into account dynamic nonlinearities (e.g., coriolis and centrifugal accelerations and payload changes), geometric nonlinearities (e.g., nonlinear coordinate-transformation matrices) and physical nonlinearities (e.g., nonlinear damping) as well as dynamic coupling in manipulators. Computer simulations are presented to indicate the effectiveness and robustness of the control scheme. When the desired trajectory is completely known before the control scheme is implemented, then off-line computations can be used to generate the adaptive feedback gains and the computational efficiency will not be a major limiting factor with this control scheme. If real-time changes in the desired trajectory have to be accommodated, the computational efficiency has to be improved using recursive relations to compute the adaptive gains. The necessary recursive relations are derived and presented in this report. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1985
Accession Number
ADA162561

Entities

People

  • C. W. Desilva
  • J. C. Van Winssen

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Compensation
  • Computational Science
  • Computations
  • Computer Simulations
  • Control Systems
  • Couplings
  • Differential Equations
  • Efficiency
  • Equations
  • Feedback
  • Frequency
  • Manipulators
  • Mechanical Engineering
  • Robots
  • Simulations

Readers

  • Control Systems Engineering.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control