Multiagent Reinforcement Learning for Active Guidance Control of Railway Vehicles with Independently Rotating Wheels

Multiagent Reinforcement Learning for Active Guidance Control of Railway Vehicles with Independently Rotating Wheels

This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel–rail wear. We base our active guidance controller on the multiagent deep deterministic policy gradient (MADDPG) al...

Full description

Bibliographic Details
Main Authors: Juyao Wei, Zhenggang Lu, Zheng Yin, Zhipeng Jing
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Applied Sciences
Subjects:
active guidance control
independently rotating wheels (IRW)
prioritized experience replay (PER)
multiagent deep deterministic policy gradient (MADDPG)
Online Access:https://www.mdpi.com/2076-3417/14/4/1677

Internet

https://www.mdpi.com/2076-3417/14/4/1677

Similar Items