TY - GEN
T1 - Fault detection based on orthotopic set membership identification for robot manipulators
AU - Reppa, Vasso
AU - Tzes, Anthony
N1 - Funding Information:
This work was partially supported by University of Patras’ K. Karatheodoris research initiative program
PY - 2008
Y1 - 2008
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
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U2 - 10.3182/20080706-5-KR-1001.1510
DO - 10.3182/20080706-5-KR-1001.1510
M3 - Conference contribution
AN - SCOPUS:79961019303
SN - 9783902661005
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
BT - Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
T2 - 17th World Congress, International Federation of Automatic Control, IFAC
Y2 - 6 July 2008 through 11 July 2008
ER -