Estimation of cutting torque in drilling system based on flexible neural network

Autor:	Shigeyasu Kawaji, Myeonghee Kim, N. Matsunaga
Rok vydání:	2004
Předmět:	Flexibility (engineering) Artificial neural network Control theory business.industry Computer science Activation function Process control Torque Artificial intelligence Fuzzy control system business
Zdroj:	Proceedings of the International Joint Conference on Neural Networks, 2003..
DOI:	10.1109/ijcnn.2003.1223439
Popis:	The use of conventional neural network in complex control applications has been limited due to its structure of low degree of freedom. In this paper, a flexible neural network (FNN), which gives flexibility of activation function, is introduced to improve the ability of the neural network, and a learning algorithm is derived. In order to show the effectiveness, the proposed method is applied to the estimation of cutting torque in a drilling process, which is a complicated control problem.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::09b36b8cf483f6300ad7ab6bff16efe6 https://doi.org/10.1109/ijcnn.2003.1223439 Zobrazit plný text záznamu