title: ÐÐ°ÑÐ°Ð¼ÐµÑÑÐ¸Ð·Ð°ÑÐ¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÑÑÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Machine learning models of friction estimation
Creators: name: ÐÐ°ÐºÑ Ð¸Ð´Ð¶Ð° Ð¥Ð°ÑÐ»Ð¸Ð¸Ð½ Ð¡Ð¸Ð½Ð³Ñ  Ð¥Ð°ÑÐ´Ð¶Ð¸Ð¸Ñ Ð¡Ð¸Ð½Ð³Ñ 
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2018
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
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Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ

description: Ð¢ÑÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð¶ÐµÑ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÑÑÑÑ Ð¸ ÐºÐ°Ðº Ð¿ÑÐµÐ¸Ð¼ÑÑÐµÑÑÐ²Ð¾, Ð¸ ÐºÐ°Ðº Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐ¾Ðº Ð² Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸ÑÑ Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð·Ð°Ð´Ð°Ñ. ÐÐ¾ ÑÐµÐ¼Ð°ÑÐ¸ÐºÐµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÐºÐ¾Ð¼Ð¿ÐµÐ½ÑÐ°ÑÐ¸Ð¸ ÑÑÐµÐ½Ð¸Ñ Ð² Ð¼ÐµÑÐ°Ð½Ð¸Ð·Ð¼Ð°Ñ Ð´Ð²Ð¸Ð³Ð°ÑÐµÐ»ÐµÐ¹ Ð±ÑÐ»Ð¸ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ñ Ð¾Ð±ÑÐ¸ÑÐ½ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ Ð¾Ð¿ÑÐ±Ð»Ð¸ÐºÐ¾Ð²Ð°Ð½ Ð·Ð½Ð°ÑÐ¸ÑÐµÐ»ÑÐ½ÑÐ¹ ÑÑÐ´ ÑÑÐ°ÑÐµÐ¹. Ð Ð½Ð°ÑÑÐ¾ÑÑÐµÐ¹ ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÐµÑÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¾ÑÐµÑÑÐ° Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÑÐµÐ½Ð¸Ñ Ñ ÑÑÐµÑÐ¾Ð¼ ÐµÐ³Ð¾ Ð¼Ð¾Ð´ÐµÐ»ÑÐ½Ð¾Ð¹ ÑÐ»Ð¾Ð¶Ð½Ð¾ÑÑÐ¸, Ð¿ÑÐ¸Ð²Ð¾Ð´ÑÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°ÑÑÐµÑÐ¾Ð², Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð½ÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ (ANN). ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ ÑÐ²Ð»ÑÑÑÑÑ Ð¼Ð¾ÑÐ½ÑÐ¼ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ¾Ð¼ Ð´Ð»Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ»Ð¾Ð¶Ð½ÑÑ Ð½ÐµÐ»Ð¸Ð½ÐµÐ¹Ð½ÑÑ Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð¸ ÑÐ²Ð»ÐµÐ½Ð¸Ð¹, Ðº ÐºÐ°ÐºÐ¸Ð¼ Ð¾ÑÐ½Ð¾ÑÐ¸ÑÑÑ ÑÑÐµÐ½Ð¸Ðµ. ÐÐ¾Ð»Ð¾Ð¶Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð¾Ð¿ÑÑ Ð² Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸ÑÐµÐ»ÑÐ½Ð¾ Ðº Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÑÐµÐ½Ð¸Ñ Ð² ÑÐµÑÐµÐ½Ð¸Ðµ Ð¿Ð¾ÑÐ»ÐµÐ´Ð½Ð¸Ñ 20 Ð»ÐµÑ ÑÑÑÐ´Ð½Ð¾ Ð¿ÐµÑÐµÐ¾ÑÐµÐ½Ð¸ÑÑ. Ð Ð´Ð°Ð½Ð½Ð¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð¿ÑÐµÐ´Ð¿ÑÐ¸Ð½ÑÑÐ° Ð¿Ð¾Ð¿ÑÑÐºÐ° ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¸Ñ ÑÑÐ¾Ð³Ð¾ Ð¾Ð¿ÑÑÐ° Ð¿Ð¾Ð´ Ð´ÑÑÐ³Ð¸Ð¼ ÑÐ³Ð»Ð¾Ð¼, Ñ ÑÐµÐ»ÑÑ Ð¾ÑÐ²ÐµÑÐ¸ÑÑ Ð½Ð° Ð²Ð¾Ð¿ÑÐ¾ÑÑ Ð¾ Ð¿Ð¾Ð·Ð¸ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÐ¸ ÑÑÐµÐ½Ð¸Ñ, Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼Ð¾ÑÑÑ Ð¿ÐµÑÐµÐºÑÐµÑÑÐ½Ð¾Ð¹ Ð¿ÑÐ¾Ð²ÐµÑÐºÐ¸ Ð¸ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÐºÑÐ¸ÑÐµÑÐ¸Ð¸ Ð´Ð»Ñ ÑÐµÐ³ÑÐ»ÑÑÐ¸Ð·Ð°ÑÐ¸Ð¸.
description: Friction can be seen both as an advantage and the other way around according to the applications. Extensive research has been made and papers have been published to model it and compensate it in the control applications. The report here talks about the study to model Friction according to its Model Complexity and it has been estimated by Artificial Neural Networks (ANN) as they are powerful tool for modeling non-linearity and Friction has been said as a complex, non-linear phenomenon. The aid of Neural Networks in assisting Friction modeling has been enormous in the last 20 years or so and the effort has been made in this study to view it from a different angle so to answer questions of position dependency of friction and to analyze the need to cross validation and Information Criteria for Regularization.