Feedforward nonlinear control using neural gas network
type: Item
instance of: scholarly article
title: Feedforward nonlinear control using neural gas network
zbMATH Open document ID: 1367.93140
DOI: 10.1155/2017/3125073
author: Iván Machón-González
author: Hilario López-García
published in: Complexity
publication date: 2017-08-03T00:00:00Z
review text: Summary: 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 piecewise 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.
Mathematics Subject Classification ID: 93B18
Mathematics Subject Classification ID: 93C10
Mathematics Subject Classification ID: 93C41
Mathematics Subject Classification ID: 93B52
Mathematics Subject Classification ID: 93B07
zbMATH DE Number: 6755965
zbMATH Keywords: feedforward nonlinear control
zbMATH Keywords: unknown dynamics
zbMATH Keywords: local linear models
zbMATH Keywords: neural gas network supervisor
zbMATH Keywords: robust clustering
zbMATH Keywords: state feedback control
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/3125073
OpenAlex ID: W2579283467
Wikidata QID: Q59142880
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description: scientific article; zbMATH DE number 6755965