Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles

Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles

This paper proposes an integrated control framework for improving the trajectory tracking performance of autonomous ground electric vehicles (AGEVs) under complex disturbances, including parameter uncertainties, and environmental changes. The framework integrates active disturbance rejection control...

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Bibliographic Details
Main Authors: Xianjian Jin, Huaizhen Lv, Yinchen Tao, Jianning Lu, Jianbo Lv, Nonsly Valerienne Opinat Ikiela
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Machines
Subjects:
autonomous vehicles
electric vehicles
vehicle dynamics
trajectory-following
active disturbance rejection control
Online Access:https://www.mdpi.com/2075-1702/13/6/523
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