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• W2103430053 abstract "We apply a maximum-likelihood stochastic system identification technique to the problem of identifying parameters of a model for friction in a hydraulic actuator. This is the first application of stochastic modelling and identification techniques to the problem of modelling friction, which is a very complex physical process. The deterministic part of the model characterizes energy dissipation mechanisms of friction and the associated transient responses. The stochastic part of the (ARMAX) model characterizes unmodelled dynamics due to process disturbances and measurement noise. The model and identification algorithm are validated by comparison with experimental data." @default.
• W2103430053 created "2016-06-24" @default.
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• W2103430053 date "2002-12-24" @default.
• W2103430053 modified "2023-09-22" @default.
• W2103430053 title "Stochastic modelling and identification of lubricated polymer friction dynamics" @default.
• W2103430053 doi "https://doi.org/10.1109/icassp.1996.550126" @default.
• W2103430053 hasPublicationYear "2002" @default.
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