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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Technology and Education Galileo da Amazônia
2025-06-01
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| Series: | ITEGAM-JETIA |
| Online Access: | http://itegam-jetia.org/journal/index.php/jetia/article/view/1672 |
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