Presentation 2007-11-19
Online Feedback Error Learning Control of Neural Network with Scaling Factor for an Inverted Pendulum
Yuzuru MORITA, Hiroshi WAKUYA,
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Abstract(in English) This paper presents an application of the feedback error learning technique for online control of an inverted pendulum system which has uncertain friction nonlinearity. In order to make possible online adaptive learning system, the preliminary training and the scaling factor for the neural network and two stages learning scheme are introduced. After some learning cycles (or epochs), responses of the plant show the minimum values that the feedback error learning scheme acts as an adaptive controller to minimize the control error. This means that the neural network acquires the inverse dynamic model of the plant through learning and then compensates the nonlinearity of the plant. The phase relationship between the output of the conventional feedback controller and the neural network is clarified. It is also shown that this control system works well for a step reference signal after learning.
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Keyword(in English) Online feedback error learning / neural network / scaling factor / inverted pendulum / nonlinear system
Paper # NC2007-66
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Committee NC
Conference Date 2007/11/11(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Online Feedback Error Learning Control of Neural Network with Scaling Factor for an Inverted Pendulum
Sub Title (in English)
Keyword(1) Online feedback error learning
Keyword(2) neural network
Keyword(3) scaling factor
Keyword(4) inverted pendulum
Keyword(5) nonlinear system
1st Author's Name Yuzuru MORITA
1st Author's Affiliation Faculty of Culture and Education, Saga University()
2nd Author's Name Hiroshi WAKUYA
2nd Author's Affiliation Faculty of Science and Engineering, Saga University
Date 2007-11-19
Paper # NC2007-66
Volume (vol) vol.107
Number (no) 328
Page pp.pp.-
#Pages 6
Date of Issue