Fault detection based on orthotopic set membership identification for robot manipulators

Vasso Reppa, Anthony Tzes

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

11 Citations (Scopus)

Abstract

In this article a fault detection algorithm for capturing structural and/or sensor failures in robot manipulators is presented. The robot dynamics is linearizable with respect to a certain parameter. Using this linearizable representation, common faults in robot arms, such as failures of actuators or faulty sensor measurements, can be identified as variations encountered in the parameter vector. The proposed algorithm uses an Orthotopic Set Membership Identifier that defines the feasible parameter set and the parameters bounds, within which the Weighted Recursive Least Square parameter estimate resides. An Output Uncertainty Predictor that generates the future region of faultless system operation. A fault is detected, when one of the following criteria below is validated: a) the WRLS parameter estimate resides out of the parameters s bounds, b) there is a sudden increase in the volume of the feasible set and c) the system s output is not within the predicted interval. Simulation studies are offered to test this fault detection methodology, customized to a two-link robot arm.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Pages7344-7349
Edition1 PART 1
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: 6 Jul 200811 Jul 2008

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Conference

Conference17th World Congress, International Federation of Automatic Control, IFAC
Country/TerritoryKorea, Republic of
CitySeoul
Period6/07/0811/07/08

Keywords

  • Bounded error identification
  • Fault detection and diagnosis

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