Advances in tilt control design of high-speed railway vehicles: a study on fuzzy control methods

Zamzuri, Hairi and Zolotas, Argyrios and Goodall, Roger and Mazlan, Saiful Amri (2012) Advances in tilt control design of high-speed railway vehicles: a study on fuzzy control methods. International Journal of Innovative Computing, Information and Control, 8 (9). pp. 6067-6080. ISSN UNSPECIFIED

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Advances in tilt control design of high-speed railway vehicles: a study on fuzzy control methods
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Abstract

The advantage of high speed trains is in the reduction of journey times between two places. Most countries developed new infrastructure to accommodate the need for high speed trains. However, this approach is rather costly. An alternative solution, which avoids new infrastructure costs and merely increases maintenance cost of current rail tracks, is to introduce tilting train technology. The main idea is tilting the vehicle body while on curved sections of the rail track. Current technologies in tilting railway vehicles use a ?precedence' control scheme; however, this increases complexity on the actual controller structure and inter-vehicle signal connections. Research on local sensor loop control strategies is still important to overcome such drawbacks. Work using conventional and modern control approaches has been investigated by previous researchers. In this paper, we propose a fuzzy correction mechanism acting as ?add-on' to enhance the capability of the controller response on curved track without compromising the effect from track irregularities on the vehicle. The fuzzy correction mechanism, as it is referred to, is applied in series with the nominal controller. Furthermore, the proposed control scheme is compared with a precedence type controller and a classical type controller to illustrate its effectiveness.

Keywords:Control Systems, Genetic algorithms, Fuzzy Logic, Tilting trains, tilt control, railway vehicles
Subjects:H Engineering > H660 Control Systems
G Mathematical and Computer Sciences > G190 Mathematics not elsewhere classified
H Engineering > H100 General Engineering
H Engineering > H332 Rail Vehicle Engineering
G Mathematical and Computer Sciences > G790 Artificial Intelligence not elsewhere classified
Divisions:College of Science > School of Engineering
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ID Code:15057
Deposited On:30 Sep 2014 08:42

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