%0 Journal Article %A Zheng, Xiang %A Zolotas, Argyrios C. %A Goodall, Roger %D 2019 %T Combined active suspension and structural damping control for suppression of flexible bodied railway vehicle vibration %U https://repository.lboro.ac.uk/articles/journal_contribution/Combined_active_suspension_and_structural_damping_control_for_suppression_of_flexible_bodied_railway_vehicle_vibration/9547067 %2 https://repository.lboro.ac.uk/ndownloader/files/17177915 %K Railway vehicle %K Active structural damping %K Active suspension control %K Frequency-weighted H2 control %K Skyhook damping %K μ analysis %K Mechanical Engineering not elsewhere classified %X The design trend for future high-speed trains is envisaged to be lightweight, rising the cost of structural vibration due to the extra flexibility. In this context, studies have looked into the suppression of such vibrations via the use of either (conventional actuators) active suspensions or by structural damping via piezoelectric actuators. The addition of extra macro-actuators will highly impact vehicle weight and is subject to location constraints, while the use of only piezo-actuators normally does not reach the required force levels for appropriate suppression. However, piezo-actuators provide appropriate complementary action with conventional active suspension. In this paper, we present a decentralised control scheme for suppressing the vertical vibration of the vehicle body, combining active structural damping via frequency-weighted H2 control and active suspension control using skyhook damping via structured H∞ synthesis. A vertical side-view model of a flexible-bodied railway vehicle is used for the control study, with the configuration of piezoelectric actuators and sensors determined via structural norms. Stability robustness of the controller is analysed with respect to parametric and dynamic uncertainties using μ analysis techniques. Results illustrate the effectiveness of the proposed control scheme for both flexible and rigid modes while guaranteeing robustness to model uncertainty. %I Loughborough University