Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F21%3A00557045" target="_blank" >RIV/60162694:G43__/21:00557045 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2076-3417/11/13/6023" target="_blank" >https://www.mdpi.com/2076-3417/11/13/6023</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app11136023" target="_blank" >10.3390/app11136023</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

Popis výsledku v původním jazyce

The energy-efficient motion control of a mobile robot fueled by batteries is an especially im-portant and difficult problem, which needs to be continually addressed in order to prolong the robot´s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly fo-cused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiments and as well as an ex-perience to navigate the DDWMR to a known destination by following the given path. Next, a full optimization process by? using the GA is operated to automatically generate the best pa-rameters of all membership functions for the FLC. To evaluate its effectiveness, a set of other well-known controllers have been implemented in Google Colab® and Jupyter platforms in Py-thon language to compare them with each other. The simulation results have shown that about 110% reduction of the energy consumption was achieved using the proposed method compared to the best of six alternative controller. Also, this simulation program has been published as an open-source code for all readers who wants to continue in the research.

Název v anglickém jazyce

Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

Popis výsledku anglicky

The energy-efficient motion control of a mobile robot fueled by batteries is an especially im-portant and difficult problem, which needs to be continually addressed in order to prolong the robot´s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly fo-cused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiments and as well as an ex-perience to navigate the DDWMR to a known destination by following the given path. Next, a full optimization process by? using the GA is operated to automatically generate the best pa-rameters of all membership functions for the FLC. To evaluate its effectiveness, a set of other well-known controllers have been implemented in Google Colab® and Jupyter platforms in Py-thon language to compare them with each other. The simulation results have shown that about 110% reduction of the energy consumption was achieved using the proposed method compared to the best of six alternative controller. Also, this simulation program has been published as an open-source code for all readers who wants to continue in the research.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21100 - Other engineering and technologies

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Applied Sciences

ISSN

2076-3417

e-ISSN

2076-3417

Svazek periodika

11

Číslo periodika v rámci svazku

13

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

23

Strana od-do

1-23

Kód UT WoS článku

000672290400001

EID výsledku v databázi Scopus

2-s2.0-85109413653