Title: A hierarchical multiple-model approach for detection and isolation of robotic actuator faults
Authors: Hsiao, Tesheng
Weng, Mao-Chiao
Department of Electrical and Computer Engineering
Keywords: Fault detection;Fault isolation;Actuator faults;Robot manipulator;Multiple model;Unscented Kalman filter;GPB-2 algorithm
Issue Date: 1-Feb-2012
Abstract: Modern robotic systems perform elaborate tasks in complicated environments and have close interactions with humans. Therefore fault detection and isolation (FDI) schemes must be carefully designed and implemented on robotic systems in order to guarantee safe and reliable operations. In this paper, we propose a hierarchical multiple-model FDI (HMM-FDI) scheme to detect and isolate actuator faults of robot manipulators. The proposed algorithm performs FDI in stages and refines the associated model set at each stage. Consequently only a small number of models are required to detect and isolate various types of unexpected actuator faults, including abrupt faults, incipient faults, and simultaneous faults. In addition, the computational load is alleviated due to the reduced-sized model set. The relation between the fault detection stage of the HMM-FDI scheme and the likelihood ratio test is explicitly revealed and theoretical upper bounds of the false alarm and missed detection probabilities are evaluated. Then we conduct experiments to demonstrate the ability of the HMM-FDI scheme in successful and immediate detection and isolation of actuator faults. (C) 2011 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.robot.2011.10.003
ISSN: 0921-8890
DOI: 10.1016/j.robot.2011.10.003
Volume: 60
Issue: 2
Begin Page: 154
End Page: 166
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