Intelligent controller design by the artificial intelligence methods

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246451" target="_blank" >RIV/61989100:27240/20:10246451 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1424-8220/20/16/4454" target="_blank" >https://www.mdpi.com/1424-8220/20/16/4454</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s20164454" target="_blank" >10.3390/s20164454</a>

Result language

angličtina

Original language name

Intelligent controller design by the artificial intelligence methods

Original language description

With the rapid growth of sensor networks and the enormous, fast-growing volumes of data collected from these sensors, there is a question relating to the way it will be used, and not only collected and analyzed. The data from these sensors are traditionally used for controlling and influencing the states and processes. Standard controllers are available and successfully implemented. However, with the data-driven era we are facing nowadays, there is an opportunity to use controllers, which can include much information, elusive for common controllers. Our goal is to propose a design of an intelligent controller-a conventional controller, but with a non-conventional method of designing its parameters using approaches of artificial intelligence combining fuzzy and genetics methods. Intelligent adaptation of parameters of the control system is performed using data from the sensors measured in the controlled process. All parts designed are based on non-conventional methods and are verified by simulations. The identification of the system&apos;s parameters is based on parameter optimization by means of its difference equation using genetic algorithms. The continuous monitoring of the quality control process and the design of the controller parameters are conducted using a fuzzy expert system of the Mamdani type, or the Takagi-Sugeno type. The concept of the intelligent control system is open and easily expandable. (C) 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20205 - Automation and control systems

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors

ISSN

1424-3210

e-ISSN

—

Volume of the periodical

20

Issue of the periodical within the volume

16

Country of publishing house

CH - SWITZERLAND

Number of pages

27

Pages from-to

1-27

UT code for WoS article

000567298300001

EID of the result in the Scopus database

2-s2.0-85089341975