A Composite Discrete/Continuous Control of Robot Manipulators

Abstract

In this report, a composite control scheme for the control of robot manipulators is proposed. Due to the modeling error or environmental uncertainties, robot motion may present a significant positioning error by using a conventional Computer-Torque Method. To improve tracking capability of robot manipulators, sliding mode control and nonlinear control algorithms have been introduced, but computation is costly, and thus a fast motion execution using simple computer sources is impossible. To solve this problem, we present a composite control algorithm to control robot motion combining a discrete feedforward component and a continuous feedback component. The discrete feed-forward component provides a nominal torque computed using the robot dynamics and compensates for dynamic between the links. This part can be updated in a large sampling time, and can be computed off-line generally, thus real time computation is decreased. The continuous feedback control component uses a structure of Variable Structure System and provides a robust control to disturbances during the sliding mode. This part can be digitally implemented using a short sampling time, and thus a fast motion of a multi-degree freedom robot manipulator can be executed by using a computer, or even a single board computer with an 8-bit CPU. The stability of the proposed multiple-rate control scheme is proven in the paper and efficiency of the control scheme has been demonstrated by simulations of a three-link robot subject to parameter and payload uncertainties.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1991
Accession Number
ADA236642

Entities

People

  • Ju-jang Lee
  • Yangsheng Xu

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Automation
  • Composite Materials
  • Computations
  • Computers
  • Control Systems
  • Couplings
  • Dynamics
  • Efficiency
  • Equations
  • Feedback
  • Frequency
  • Lyapunov Functions
  • Manipulators
  • Sampling
  • Simulations
  • Uncertainty

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • 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