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A PLS-Based Statistical Approach for Fault Detection and Isolation of Robotic Manipulators

【摘要】 In this paper, a statistical approach to fault detection and isolation (FDI) of robot manipulators is presented. It is based on a statistical method called partial least squares (PLS) and on the inverse dynamic model of a robot. PLS is a well-established linear technique in process control for identifying and monitoring industrial plants. Since a robot inverse dynamics can be represented as a linear static model in the dynamical parameters, it is possible to use algorithms and confidence regions developed in statistical decision theory. This approach has several advantages with respect to standard FDI modules: It is strictly related to the algorithm used for identifying the dynamical parameters, it does not need to solve at run time a set of nonlinear differential equations, and the design of a nonlinear observer is not required. This method has been tested on a PUMA 560 simulator, and results of the simulations are discussed.

【期刊名称】 Industrial Electronics, IEEE Transactions on

【作者】 Muradore R.;

【作者单位】

【收录信息】

【年(卷),期】2012(59),8

【年度】2012

【页码】p.3167-3175

【总页数】9

【原文格式】PDF

【正文语种】eng

【中图分类】

【原文服务方】国家工程技术数字图书馆

【关键词】

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