The coupling of magnetorheological (MR) dampers with semi-active control schemes has proven to be an effective and failsafe approach for vibration mitigation of low-damped structures. However, due to the nonlinearities inherently relating to such damping devices, the characterization of the associated nonlinear phenomena is still a challenging task. Herein, an enhanced phenomenological modeling approach is proposed for the description of a rotationaltype MR damper, which comprises a modified Bouc-Wen model coupled with an appropriately selected sigmoid function. In a first step, parameter optimization is performed on the basis of individual models in an effort to approximate the experimentally observed response for varying current levels and actuator force characteristics. In a second step, based on the previously identified parameters, a generalized best-fit model is proposed by performing a regression analysis. Finally, model validation is carried out via implementation on different sets of experimental data. The proposed model indeed renders an improved representation of the actually observed nonlinear behavior of the tested rotational MR damper.

This study introduces a novel semi-active control scheme, where the linear-quadratic regulator (LQR) is combined with an unscented Kalman filter (UKF) observer, for the real-time mitigation of structural vibration. Due to a number of factors, such as environmental effects and ageing processes, the controlled system may be characterized by uncertainties. The UKF, which comprises a nonlinear observer, is employed herein for devising an adaptive semi-active control scheme capable of tackling such a challenge. This is achieved through the real-time realization of joint state and parameter estimation during the structural control process via the proposed LQR-UKF approach. The behavior of the introduced scheme is exemplified through two numerical applications. The efficacy of the devised methodology is firstly compared against the standard LQR-KF approach in a linear benchmark application where the system model is assumed known a priori, and secondly, the method is validated on a joint state and parameter estimation problem where the system model is assumed uncertain, formulated as nonlinear, and updated in real-time.

SUMMARYThis study performs an experimental investigation of a novel, semi-active control strategy for effective vibration mitigation. The implemented approach comprises a combination of the linear quadratic regulator with a nonlinear observer, namely, the unscented Kalman filter, for the control of systems described by uncertainties. Indeed, numerical models of structural systems often result as inadequate because of inherent uncertainties, such as noise, modeling errors, unknown system properties, or influence of varying operational and environmental conditions. In tackling this issue, the unscented Kalman filter is herein employed for adaptive joint state and parameter estimation refining the accuracy of the model employed by the controller and resulting in enhanced vibration mitigation. A scaled five-story shear frame attached to a hydraulic cylinder comprises the tested structure, where actuation is provided by means of a rotational magnetorheological damper operating on the relative motion between the ground floor and the first floor plate. The experimentally obtained results demonstrate a good agreement with simulations and encourage further implementation of the proposed framework in field applications of structural control.

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This study performs a series of numerical investigations of a novel energy-based control approach for effective vibration control of clustered tensegrity structures via different optimal active control algorithms. The comparative study among different control algorithms of clustered tensegrities are often challenging due to the geometrical non-linearity, complex loading conditions and assemblage uncertainties of structural components. In order to overcome these technical difficulties, an actuator input energy-based method is herein implemented to assess the optimal dynamic performances of clustered tensegrity structures via distinct optimal active control schemes. As a quantification tool, the structural displacement and elemental forces monitored from both the whole structure level and the elemental level were applied to assess control efficiency based on the same amount of actuator energy input. Specifically, the control efficiency comparisons are realized by setting identical energy input to actuated elements via linear-quadratic-Gaussian (LQG) and  ∞ algorithms. Different actuator placements of clustered cables and struts are considered and the control efficiency coefficients of the proposed method are examined through a spatial clustered tensegrity beam. The outcomes from the illustrative example indicate that the proposed method is efficient and reliable in comparative analyzing of different optimal active control schemes for clustered tensegrity structures, which implies the prospect of the investigated approach in analyzing and solving actual engineering problems. KEYWORDS active control algorithms, actuator placements, clustered tensegrity structures, control efficiency, energy-based control Struct Control Health Monit. 2018;25:e2215.wileyonlinelibrary.com/journal/stc