On-line adaptive control of robot manipulators using dynamic fuzzy neural networks

Gao, Yang and Er, M.J. and Leithead, W.E. and Leith, D.J. (2001) On-line adaptive control of robot manipulators using dynamic fuzzy neural networks. In: American Control Conference, 2001-06-25 - 2001-06-27.

Abstract

This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for motion control of a multilink robot manipulator. The proposed controller has the following salient features: (1) dynamic fuzzy neural networks structure, i.e. fuzzy control rules can be generated or deleted automatically, (2) adaptive learning, (3) online learning of the robot dynamics, (4) fast learning speed, and (5) fast convergence of tracking error. Global stability of the system is established using Lyapunov approach. Computer simulation studies of a two-link robot manipulator demonstrate that excellent tracking performance can be achieved under external disturbances

• Share and Export
  

  ASCII CitationEP3 XMLRIS (EndNote Online, Zotero, Ref manager, etc)HTML CitationOpenURL ContextObject in SpanRIOXX2 XMLRDF+N-TriplesBibTeXMPEG-21 DIDLMODSRefWorksRDF+N3Multiline CSVJSONDublin CoreData Cite XMLSimple MetadataEndNoteAtomMETSOpenURL ContextObjectRDF+XMLRefer
• Item metadata

  Item type:	Conference or Workshop Item(Paper)
  ID code:	37525
  Dates:	Date Event 27 June 2001 Published
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	09 Feb 2012 14:40
  Last modified:	11 Nov 2024 16:25
  URI:	https://strathprints.strath.ac.uk/id/eprint/37525