제어로봇시스템학회:학술대회논문집
- 2001.10a
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- Pages.47.1-47
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- 2001
Thrust Force Estimation using Flexible Neural Networks
- Kim, Myeong-Hee (Kumamoto Univ.) ;
- Shigeyasu Kawaji (Kumamoto Univ.) ;
- Masaki Arao (Social System Business Company)
- Published : 2001.10.01
Abstract
The drilling process has a great importance for the production technology due to its widerspread use in the manufacturing industry. In order to enhance a maximum production rate and prevent the drill from the damage, it is important to monitor and control the drilling system. Thrust force and cutting torque are the main output variables in the design of drilling control systems. In this paper, an alternative estimation method of thrust force by using flexible neural networks is proposed. Flexible neural network uses the sigmoid activation function with adjustable parameter in order to enhance the approximation accuracy ...
Keywords