Neural network and fuzzy control techniques for robotic systems

Kazuo Kiguchi, Keigo Watanabe, Toshio Fukuda

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter, advanced neural network and fuzzy control techniques for robotic systems such as robot manipulators are introduced. Position/force control is one of the most important and fundamental operations of robot manipulators to perform sophisticated tasks. It is known that neural network and fuzzy control techniques are very effective for position/force control, especially in an unknown/uncertain environment. By applying these soft computing techniques, undesired overshooting and oscillation caused by the unknown/uncertain dynamics of a robot manipulator and an object/environment can be decreased efficiently and precise position/force control can be realized.

Original languageEnglish
Title of host publicationIntelligent Systems
Subtitle of host publicationTechnology and Applications, Six Volume Set
PublisherCRC Press
PagesII-73-II-95
ISBN (Electronic)9781420040814
ISBN (Print)0849311217, 9780849311215
Publication statusPublished - Jan 1 2002
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

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  • Cite this

    Kiguchi, K., Watanabe, K., & Fukuda, T. (2002). Neural network and fuzzy control techniques for robotic systems. In Intelligent Systems: Technology and Applications, Six Volume Set (pp. II-73-II-95). CRC Press.