Active Steering Controller for Driven Independently Rotating Wheelset Vehicles Based on Deep Reinforcement Learning

This paper proposes an active steering controller for Driven Independently Rotating Wheelset (DIRW) vehicles based on deep reinforcement learning (DRL). For the two-axle railway vehicles equipped with Independently Rotating Wheelsets (IRWs), each wheel connected to a wheel-side motor, the Ape-X DDPG...

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Vydáno v:Processes Ročník 11; číslo 9; s. 2677
Hlavní autoři: Lu, Zhenggang, Wei, Juyao, Wang, Zehan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.09.2023
Témata:
Active control
Algorithms
Control algorithms
Control theory
Controllers
Deep learning
Design
Digital twins
Dynamic models
Efficiency
H-infinity control
Machine learning
Neural networks
Product enhancement
Railway tracks
Reinforcement
Robotics
Robust control
Rotation
Scale models
Steering
Trains
Vehicles
Wheels
Wheelsets
ISSN:2227-9717, 2227-9717
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Shrnutí:This paper proposes an active steering controller for Driven Independently Rotating Wheelset (DIRW) vehicles based on deep reinforcement learning (DRL). For the two-axle railway vehicles equipped with Independently Rotating Wheelsets (IRWs), each wheel connected to a wheel-side motor, the Ape-X DDPG controller, an enhanced version of the Deep Deterministic Policy Gradient (DDPG) algorithm, is adopted. Incorporating Distributed Prioritized Experience Replay (DPER), Ape-X DDPG trains neural network function approximators to obtain a data-driven DIRW active steering controller. This controller is utilized to control the input torque of each wheel, aiming to improve the steering capability of IRWs. Simulation results indicate that compared to the existing model-based H∞ control algorithm and data-driven DDPG control algorithm, the Ape-X DDPG active steering controller demonstrates better curving steering performance and centering ability in straight tracks across different running conditions and significantly reduces wheel–rail wear. To validate the proposed algorithm’s efficacy in real vehicles, a 1:5 scale model of the DIRW vehicle and its digital twin dynamic model were designed and manufactured. The proposed control algorithm was deployed on the scale vehicle and subjected to active steering control experiments on a scaled track. The experimental results reveal that under the active steering control of the Ape-X DDPG controller, the steering performance of the DIRW scale model on both straight and curved tracks is significantly enhanced.
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ISSN:2227-9717
2227-9717
DOI:10.3390/pr11092677