Detail publikace

Design of fuzzy logic controller for DC motor

ANDRŠ, O. BŘEZINA, T. KOVÁŘ, J.

Český název

Design of fuzzy logic controller for DC motor

Anglický název

Design of fuzzy logic controller for DC motor

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

en

Originální abstrakt

This contribution presents a simple and efficient approach to the fuzzy logic controller design and simulation. The proposed controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design meth-od is based on anfis (adaptive neuro-fuzzy inference system) training rou-tine. It utilizes a combination of the least-squares method and the back-propagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controller is used for the position control of a linear actuator which is a part of a Stewart platform.

Český abstrakt

This contribution presents a simple and efficient approach to the fuzzy logic controller design and simulation. The proposed controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design meth-od is based on anfis (adaptive neuro-fuzzy inference system) training rou-tine. It utilizes a combination of the least-squares method and the back-propagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controller is used for the position control of a linear actuator which is a part of a Stewart platform.

Anglický abstrakt

This contribution presents a simple and efficient approach to the fuzzy logic controller design and simulation. The proposed controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design meth-od is based on anfis (adaptive neuro-fuzzy inference system) training rou-tine. It utilizes a combination of the least-squares method and the back-propagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controller is used for the position control of a linear actuator which is a part of a Stewart platform.

Klíčová slova česky

fuzzy logic, controller

Klíčová slova anglicky

fuzzy logic, controller

Rok RIV

2011

Vydáno

21.09.2011

Nakladatel

Springer

Místo

Varšava

ISBN

978-3-642-23243-5

Kniha

Mechatronics Recent Technological and Scientific Advances

Číslo edice

1

Strany od–do

9–18

Počet stran

10

BIBTEX


@inproceedings{BUT73751,
  author="Ondřej {Andrš} and Tomáš {Březina} and Jiří {Kovář},
  title="Design of fuzzy logic controller for DC motor",
  booktitle="Mechatronics Recent Technological and Scientific Advances",
  year="2011",
  month="September",
  pages="9--18",
  publisher="Springer",
  address="Varšava",
  isbn="978-3-642-23243-5"
}