LOG and GA solutions for active steering of railway vehicles

T. X. Mei, R. M. Goodall

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

The paper presents control strategies for the active steering of solid axle railway vehicles using the linear quadratic Gaussian (LQG) method. The paper investigates the benefits of actively controlling and steering the wheelsets of a railway vehicle and studies what could be achieved when modern control techniques are used on the vehicles via mechatronic components. An optimal H2 controller is developed for the active steering and is fine-tuned using genetic algorithms. A Kaiman filter is developed to provide the full state feedback required by the optimal control. The Kaiman filter is formulated in such a way that it not only estimates all the vehicle states, but also calculates parameters such as curve radius and cant of the railway track on which the vehicle is travelling. Computer simulations are used in the study to assess the system performance with the control scheme proposed.

LanguageEnglish
Pages111-117
Number of pages7
JournalIEE Proceedings: Control Theory and Applications
Volume147
Issue number1
DOIs
Publication statusPublished - 1 Jan 2000
Externally publishedYes

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vehicles
filters
Mechatronics
Axles
optimal control
State feedback
genetic algorithms
controllers
computerized simulation
Genetic algorithms
slopes
Controllers
radii
Computer simulation
curves
estimates

Cite this

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title = "LOG and GA solutions for active steering of railway vehicles",
abstract = "The paper presents control strategies for the active steering of solid axle railway vehicles using the linear quadratic Gaussian (LQG) method. The paper investigates the benefits of actively controlling and steering the wheelsets of a railway vehicle and studies what could be achieved when modern control techniques are used on the vehicles via mechatronic components. An optimal H2 controller is developed for the active steering and is fine-tuned using genetic algorithms. A Kaiman filter is developed to provide the full state feedback required by the optimal control. The Kaiman filter is formulated in such a way that it not only estimates all the vehicle states, but also calculates parameters such as curve radius and cant of the railway track on which the vehicle is travelling. Computer simulations are used in the study to assess the system performance with the control scheme proposed.",
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LOG and GA solutions for active steering of railway vehicles. / Mei, T. X.; Goodall, R. M.

In: IEE Proceedings: Control Theory and Applications, Vol. 147, No. 1, 01.01.2000, p. 111-117.

Research output: Contribution to journalArticle

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