Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning

Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning

The integration of automated guided vehicles (AGVs) in industrial automation demands precise and adaptive control systems for efficient path tracking. This study introduces a hybrid framework combining traditional Proportional-Integral-Derivative (PID) control with advanced machine learning to optim...

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Bibliographic Details
Main Authors: Kinza Nazir, Yong-Woon Kim, Yung-Cheol Byun
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Automated guided vehicle
genetic algorithm
machine learning
path tracking
support vector regression
Online Access:https://ieeexplore.ieee.org/document/10960296/
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https://ieeexplore.ieee.org/document/10960296/

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