All-Wheel Steering Tracking Control Method for Virtual Rail Trains with Only Interoceptive Sensors

A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban r...

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Bibliographic Details
Published in:World electric vehicle journal 2024-06, Vol.15 (6), p.247
Main Authors: Wang, Zhenpo, Zhang, Yi, Wang, Zhifu
Format: Article
Language:English
Subjects:
Actuators
Algorithms
all-wheel steering
Cameras
Construction costs
Control methods
Controllers
Data compression
Economic impact
Hardware-in-the-loop simulation
interoceptive sensors
Kinematics
Light rail transportation
Methods
Public transportation
Roads & highways
Sensors
Shafts (machine elements)
Steering
Tracking control
Transportation systems
Vehicles
virtual rail train
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Summary:A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban roads easily. This paper proposed a tracking control approach using only interoceptive sensors with high scene adaptivity. The kinematic model was established first under reasonable assumptions when the sensor configuration was completed simultaneously. A hierarchical controller consists of a front axle controller and a rear axle controller. The former applies virtual axles theory to avoid motion interference. The latter generates a first-axle reference path with path segmentation and a data updating method to improve storage and computational efficiency. Then, a fast curvature matching rear axles control method is developed with an actuator time delay considered. Finally, the proposed approach is verified in a hardware in loop (HIL) simulation under various situations with predefined evaluation standards, which shows better tracking performance and applicability.
ISSN:2032-6653
2032-6653
DOI:10.3390/wevj15060247