Fault detection based on orthotopic set membership identification for robot manipulators

Vasso Reppa, Antonios Tzes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 (US)
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Volume17
Edition1 PART 1
DOIs
StatePublished - Dec 1 2008
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: Jul 6 2008Jul 11 2008

Other

Other17th World Congress, International Federation of Automatic Control, IFAC
CountryKorea, Republic of
CitySeoul
Period7/6/087/11/08

Fingerprint

Fault detection
Manipulators
Robots
Sensors
Actuators

Keywords

  • Bounded error identification
  • Fault detection and diagnosis

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Reppa, V., & Tzes, A. (2008). Fault detection based on orthotopic set membership identification for robot manipulators. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (1 PART 1 ed., Vol. 17) https://doi.org/10.3182/20080706-5-KR-1001.1510

Fault detection based on orthotopic set membership identification for robot manipulators. / Reppa, Vasso; Tzes, Antonios.

Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. Vol. 17 1 PART 1. ed. 2008.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Reppa, V & Tzes, A 2008, Fault detection based on orthotopic set membership identification for robot manipulators. in Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. 1 PART 1 edn, vol. 17, 17th World Congress, International Federation of Automatic Control, IFAC, Seoul, Korea, Republic of, 7/6/08. https://doi.org/10.3182/20080706-5-KR-1001.1510
Reppa V, Tzes A. Fault detection based on orthotopic set membership identification for robot manipulators. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. 1 PART 1 ed. Vol. 17. 2008 https://doi.org/10.3182/20080706-5-KR-1001.1510
Reppa, Vasso ; Tzes, Antonios. / Fault detection based on orthotopic set membership identification for robot manipulators. Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. Vol. 17 1 PART 1. ed. 2008.
@inproceedings{660e92949d9d4968a5f98a959323c3d7,
title = "Fault detection based on orthotopic set membership identification for robot manipulators",
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.",
keywords = "Bounded error identification, Fault detection and diagnosis",
author = "Vasso Reppa and Antonios Tzes",
year = "2008",
month = "12",
day = "1",
doi = "10.3182/20080706-5-KR-1001.1510",
language = "English (US)",
isbn = "9783902661005",
volume = "17",
booktitle = "Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC",
edition = "1 PART 1",

}

TY - GEN

T1 - Fault detection based on orthotopic set membership identification for robot manipulators

AU - Reppa, Vasso

AU - Tzes, Antonios

PY - 2008/12/1

Y1 - 2008/12/1

N2 - 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.

AB - 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.

KW - Bounded error identification

KW - Fault detection and diagnosis

UR - http://www.scopus.com/inward/record.url?scp=79961019303&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79961019303&partnerID=8YFLogxK

U2 - 10.3182/20080706-5-KR-1001.1510

DO - 10.3182/20080706-5-KR-1001.1510

M3 - Conference contribution

AN - SCOPUS:79961019303

SN - 9783902661005

VL - 17

BT - Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC

ER -