Multiple Fuzzy Control of a Robot Manipulator

Sangho Jin, Keigo Watanabe, Masatoshi Nakamura

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A learning fuzzy controller is described for controlling a robot manipulator. The learning controller used here is called a multiple fuzzy controller, in which several elemental fuzzy controllers are processed in parallel and the degree of usage of each inferred consequent is determined by using a linear neural network. Two learning algorithms are considered in the framework of the specialized learning architecture : one is based on minimizing the squared sum of the trajectory error for each link and the other is based on directly minimizing the trajectory squared error for each link. The effectiveness of the proposed controller is illustrated by making some simulations for a two-link manipulator.

Original languageEnglish
Pages (from-to)158-164
Number of pages7
Journaltransactions of the japan society of mechanical engineers series c
Volume59
Issue number557
DOIs
Publication statusPublished - Jan 1 1993
Externally publishedYes

Keywords

  • Automatic Control
  • Computer Control
  • Fuzzy Control
  • Iterative Learning Control
  • Multiple Controllers
  • Robotics
  • Self-Organizing

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'Multiple Fuzzy Control of a Robot Manipulator'. Together they form a unique fingerprint.

  • Cite this