Two fault detection and isolation schemes for robot manipulators using soft computing techniques

Yueksel T., Sezgin A.

APPLIED SOFT COMPUTING, vol.10, no.1, pp.125-134, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 10 Issue: 1
  • Publication Date: 2010
  • Doi Number: 10.1016/j.asoc.2009.06.011
  • Journal Name: APPLIED SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.125-134
  • Keywords: Fault detection and isolation, M-ANFIS, Neural networks, Robot manipulators, FUZZY-LOGIC, RESIDUAL GENERATION, DIAGNOSIS, SUPERVISION
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

With growing technology, fault detection and isolation (FDI) have become one of the interesting and important research areas in modern control and signal processing. Accomplishment of specific missions like waste treatment in nuclear reactors or data collection in space and underwater missions make reliability more important for robotics and this demand forces researchers to adapt available FDI studies on nonlinear systems to robot manipulators, mobile robots and mobile manipulators.