Fully Automatic Operation Algorithm of Urban Rail Train Based on RBFNN Position Output Constrained Robust Adaptive Control

Fully Automatic Operation Algorithm of Urban Rail Train Based on RBFNN Position Output Constrained Robust Adaptive Control

High parking accuracy, comfort and stability, and fast response speed are important indicators to measure the control performance of a fully automatic operation system. In this paper, aiming at the problem of low accuracy of the fully automatic operation control of urban rail trains, a radial basis...

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Bibliographic Details
Main Authors: Junxia Yang, Youpeng Zhang, Yuxiang Jin
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Algorithms
Subjects:
fully automatic operation system (FAO)
radial basis function neural network (RBFNN)
position output constrained control
adaptive control
tracking error
Online Access:https://www.mdpi.com/1999-4893/14/9/264

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https://www.mdpi.com/1999-4893/14/9/264

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