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Failure detection and isolation in robotic manipulators using joint torque sensors

Published online by Cambridge University Press:  24 June 2009

Mehrzad Namvar  and
Farhad Aghili
Mehrzad Namvar*
Affiliation:
Department of Electrical Engineering, Sharif University of Technology, P.O. Box 11155-8639, Tehran, Iran
Farhad Aghili
Affiliation:
Canadian Space Agency, St. Hubert, Quebec, CanadaJ3Y 8Y9
*
*Corresponding author. E-mail: [email protected]
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Summary

Reliability of any model-based failure detection and isolation (FDI) method depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities such as friction, backlash, and flexibilities. In this paper, we show that the application of the simplified model in a fault detection algorithm increases reliability of fault monitoring system against modeling uncertainty. The proposed FDI filter is based on a smooth velocity observer of degree 2n where n stands for the number of manipulator joints. No velocity measurement and assumptions on smoothness of faults are used in the fault detection process. The paper focuses on actuator faults and investigates the effect of torque sensor noise on threshold selection. The FDI filter is further improved to become robust against an unknown bias in torque sensor reading. The effect of position sensor noise together with position sensor faults are also investigated. Simulation example on a 6-degrees of freedom manipulator is carried out to illustrate the performance of the proposed FDI method.

Keywords

Robotic self-diagnosisFault detection and IsolationJoint torque sensingControl of robotic systemsActuator and sensor faults
Type
Article
Information
Robotica , Volume 28 , Issue 4 , July 2010 , pp. 549 - 561
Copyright
Copyright © Cambridge University Press 2009

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