Inverse Model Approximation Using Iterative Method and Neural Networks with Practical Application for Unstable Nonlinear System Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F19%3APU130441" target="_blank" >RIV/00216305:26210/19:PU130441 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Inverse Model Approximation Using Iterative Method and Neural Networks with Practical Application for Unstable Nonlinear System Control
Original language description
In this paper a method for controlling and stabilizing an unstable nonlinear system using a NARX neural network is presented. It is difficult to design a common feedback controller or even perform system identification on unstable systems, more even so if these systems are nonlinear. To compensate for nonlinearity a feedforward controller is required. In this paper we present a method of estimating inverse model of the system for the feedforward controller using a NARX artificial neural network in an iterative approach which takes less time than methods commonly used and performs as good. This method is verified and tested on an educational model of magnetic levitation of steel ball. Both static and dynamic forms of the inverse model are presented and evaluated with positive results.
Czech name
—
Czech description
—

Project
—
Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
PROCEEDINGS OF THE 2018 18TH INTERNATIONAL CONFERENCE ON MECHATRONICS - MECHATRONIKA (ME)
ISBN
978-80-214-5542-9
ISSN
—
e-ISSN
—
Number of pages
7
Pages from-to
209-215
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Brno
Event date
Dec 5, 2018
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000465104200033

Similar results(10)