Feedforward Nonlinear Control Using Neural Gas Network
Joint Authors
Machón-González, Iván
López-García, Hilario
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-15
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Nonlinear systems control is a main issue in control theory.
Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems.
This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network.
The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure.
The direct model of the plant constitutes a piece-wise linear approximation of the nonlinear system and each neuron represents a local linear model for which a linear controller is designed.
The neural gas model works as an observer and a controller at the same time.
A state feedback control is implemented by estimation of the state variables based on the local transfer function that was provided by the local linear model.
The gradient vectors obtained by the supervised neural gas algorithm provide a robust procedure for feedforward nonlinear control, that is, supposing the inexistence of disturbances.
American Psychological Association (APA)
Machón-González, Iván& López-García, Hilario. 2017. Feedforward Nonlinear Control Using Neural Gas Network. Complexity،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142685
Modern Language Association (MLA)
Machón-González, Iván& López-García, Hilario. Feedforward Nonlinear Control Using Neural Gas Network. Complexity No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1142685
American Medical Association (AMA)
Machón-González, Iván& López-García, Hilario. Feedforward Nonlinear Control Using Neural Gas Network. Complexity. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1142685
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142685