Optimized PID Tuning in Longitudinal Control of Electric Autonomous Vehicles: A Comparative Study of Jellyfish Search and Genetic Algorithm

Optimized PID Tuning in Longitudinal Control of Electric Autonomous Vehicles: A Comparative Study of Jellyfish Search and Genetic Algorithm

Tuning PID controllers to enhance longitudinal control and speed planning of Electric Autonomous Vehicles is a challenge, which can be effectively addressed by evolving metaheuristic algorithms. This paper evaluates the performance of the Jellyfish Search (JS) optimizer and Genetic Algorith...

Full description

Saved in:
Bibliographic Details
Main Authors: Asmaa Guendouz, Mustapha Hatti, Abdelhalim Tlemçani
Format: Article
Language:English
Published: Institute of Technology and Education Galileo da Amazônia 2025-06-01
Series:ITEGAM-JETIA
Online Access:http://itegam-jetia.org/journal/index.php/jetia/article/view/1672
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items