Robust system state estimation for active suspension control in high-speed tilting trains

Zhou, Ronghui, Zolotas, Argyrios and Goodall, Roger (2014) Robust system state estimation for active suspension control in high-speed tilting trains. Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility, 52 (Supp 1). pp. 355-369. ISSN 0042-3114

15026 VSD_paper_2014x2_Ronghui.pdf
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Item Type:Article
Item Status:Live Archive


The interaction between the railway vehicle body roll and lateral dynamics substantially influences the tilting system performance in high-speed tilting trains, which results in a potential poor ride comfort and high risk of motion sickness. Integrating active lateral secondary suspension into the tilting control system is one of the solutions to provide a remedy to roll?lateral interaction. It improves the design trade-off for the local tilt control (based only upon local vehicle measurements) between straight track ride comfort and curving performance. Advanced system state estimation technology can be applied to further enhance the system performance, i.e. by using the estimated vehicle body lateral acceleration (relative to the track) and true cant deficiency in the configuration of the tilt and lateral active suspension controllers, thus to further attenuate the system dynamics coupling. Robust H-inf filtering is investigated in this paper aiming to offer a robust estimation (i.e. estimation in the presence of uncertainty) for the required variables, In particular, it can minimise the maximum estimation error and thus be more robust to system parametric uncertainty. Simulation results illustrate the effectiveness of the proposed schemes.

Additional Information:Special issue: IAVSD Proceeding Supplement
Keywords:Robustness (control systems), Active suspension control systems, tilt control, integrated suspension control, NotOAChecked
Subjects:H Engineering > H660 Control Systems
H Engineering > H100 General Engineering
H Engineering > H332 Rail Vehicle Engineering
Divisions:College of Science > School of Engineering
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ID Code:15026
Deposited On:24 Sep 2014 08:06

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