NDLI: Detection and identification of actuator faults in robotic systems based on multiple-model nonlinear state estimation

Content Provider	IEEE Xplore Digital Library
Author	Tesheng Hsiao Huei-jyun Haung
Copyright Year	2009
Description	Author affiliation: Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan (Tesheng Hsiao; Huei-jyun Haung)
Abstract	Modern robotic systems perform elaborate tasks in a complicated environment and have close interactions with humans. Therefore fault detection and isolation (FDI) systems must be carefully designed and implemented on robots in order to guarantee safe and reliable operations. In addition, many high performance robotic controllers require full state feedback; hence it is essential to implement state estimators whenever not all state variables are measurable. Moreover, the state estimator must work properly despite the presence of faults so that the robot is fault tolerable. In this paper, we propose an algorithm for state estimation, fault detection, and fault identification of a robotic system. All faults in consideration are associated with a set of exclusive fault modes. Then a multiple-model nonlinear state estimator is applied to estimate not only the state but also the fault mode of the robot at each time step. Furthermore all fault modes are organized in a hierarchical structure to alleviate the computation load. Simulations show that state estimation is accurate even in the event of actuator faults, and that the occurrence of faults is detected immediately. The computational advantage of the proposed hierarchical structure is also demonstrated by the simulations.
Starting Page	688
Ending Page	693
File Size	624334
Page Count	6
File Format	PDF
ISBN	9781424446841
DOI	10.1109/MED.2009.5164623
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-24
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Actuators State feedback Event detection Computational modeling Robot control Human robot interaction Discrete event simulation unscented Kalman filter Fault diagnosis robot Fault detection GPB-2 algorithm State estimation fault detection and isolation
Content Type	Text
Resource Type	Article

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