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Fuzzy Fine tuning of an Optimized PID Control Scheme for Mobile Robot Trajectory Tracking

by Turki Y. Abdalla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 19
Year of Publication: 2018
Authors: Turki Y. Abdalla
10.5120/ijca2018917875

Turki Y. Abdalla . Fuzzy Fine tuning of an Optimized PID Control Scheme for Mobile Robot Trajectory Tracking. International Journal of Computer Applications. 181, 19 ( Sep 2018), 15-19. DOI=10.5120/ijca2018917875

@article{ 10.5120/ijca2018917875,
author = { Turki Y. Abdalla },
title = { Fuzzy Fine tuning of an Optimized PID Control Scheme for Mobile Robot Trajectory Tracking },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 181 },
number = { 19 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number19/29971-2018917875/ },
doi = { 10.5120/ijca2018917875 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:24.451785+05:30
%A Turki Y. Abdalla
%T Fuzzy Fine tuning of an Optimized PID Control Scheme for Mobile Robot Trajectory Tracking
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 19
%P 15-19
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper present an efficient robust design method of PID control scheme based on using fuzzy logic and particles swarm optimization (PSO) method for trajectory tracking of mobile robot. Two PID controllers are used. Parameters of PID controllers are optimized offline using PSO and fuzzy controller is used for tuning the parameters online . The two optimized PID controllers are used for speed control and azimuth control. The online fuzzy tuning in the designed control scheme work well when there are variations in the plant parameters and changes in operating conditions.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobile Robot Particles Swarm Optimization fuzzy control PID Controller Trajectory tracking.