A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonline...

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Main Author: Ahmed Sabah Al-Araji
Format: Article
Language:English
Published: University of Baghdad 2023-07-01
Series:Journal of Engineering
Subjects:
Online Access:https://joe.uobaghdad.edu.iq/index.php/main/article/view/2143
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author Ahmed Sabah Al-Araji
author_facet Ahmed Sabah Al-Araji
author_sort Ahmed Sabah Al-Araji
collection DOAJ
description This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO learning algorithm is more effective and robust than genetic learning algorithm; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied.
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spelling doaj.art-de83ed78cd9e403a90ef6e61c0633d2b2023-07-11T18:34:18ZengUniversity of BaghdadJournal of Engineering1726-40732520-33392023-07-01200510.31026/j.eng.2014.05.03A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot ModelAhmed Sabah Al-Araji This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO learning algorithm is more effective and robust than genetic learning algorithm; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied. https://joe.uobaghdad.edu.iq/index.php/main/article/view/2143genetic algorithm, particle swarm optimization, nonlinear PID controller, NI mobile robots, trajectory tracking.
spellingShingle Ahmed Sabah Al-Araji
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
Journal of Engineering
genetic algorithm, particle swarm optimization, nonlinear PID controller, NI mobile robots, trajectory tracking.
title A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
title_full A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
title_fullStr A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
title_full_unstemmed A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
title_short A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
title_sort comparative study of various intelligent algorithms based nonlinear pid neural trajectory tracking controller for the differential wheeled mobile robot model
topic genetic algorithm, particle swarm optimization, nonlinear PID controller, NI mobile robots, trajectory tracking.
url https://joe.uobaghdad.edu.iq/index.php/main/article/view/2143
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