Fault tolerant control for robot manipulators using neural network and second-order sliding mode observer

Mien Van, Hee-Jun Kang

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

1 Citation (Scopus)

Abstract

This paper investigates an algorithm for fault tolerant control of uncertain robot manipulator with only joint position measurement using neural network and second-order sliding mode observer. First, a neural network (NN) observer is designed to estimate the modeling uncertainties. Based on the obtained uncertainty estimation, a second-order sliding mode observer is then designed for two purposes: 1) Providing the velocity estimation, 2) providing the fault information that is used for fault detection, isolation and identification. Finally, a fault tolerant control scheme is proposed for compensating the effect of uncertainties and faults based on the fault estimation information. Computer simulation results on a PUMA560 industrial robot are shown to verify the effectiveness of the proposed strategy.
Original languageEnglish
Title of host publication International Conference on Intelligent Computing, China, 2013
PublisherSpringer Lecture Notes in Computer Science (LNCS)
Pages526-535
Volume7995
DOIs
Publication statusPublished - 2013

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