Adaptive Neuro-fuzzy approach in friction identification

被引：0
|
作者：
Ismail, Muhammad Zaiyad Muda [1 ]
机构：
[1] Univ Teknol MARA, Fak Kejuruteraan Mekan, Shah Alam, Selangor, Malaysia
来源：
4TH INTERNATIONAL CONFERENCE ON MANUFACTURING, OPTIMIZATION, INDUSTRIAL AND MATERIAL ENGINEERING (MOIME 2016) | 2016年 / 131卷
关键词：
D O I：
10.1088/1757-899X/131/1/012015
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Friction is known to affect the performance of motion control system, especially in terms of its accuracy. Therefore, a number of techniques or methods have been explored and implemented to alleviate the effects of friction. In this project, the Artificial Intelligent (AI) approach is used to model the friction which will be then used to compensate the friction. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is chosen among several other AI methods because of its reliability and capabilities of solving complex computation. ANFIS is a hybrid AI-paradigm that combines the best features of neural network and fuzzy logic. This AI method (ANFIS) is effective for nonlinear system identification and compensation and thus, being used in this project.
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页数：6
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