000013782 001__ 13782
000013782 005__ 20161114170255.0
000013782 04107 $$aeng
000013782 046__ $$k2011-05-25
000013782 100__ $$aBhowmik, S.
000013782 24500 $$aNeural Network Based Semi-Active Control Strategy for Structural Vibration Mitigation with Magnetorheological Damper

000013782 24630 $$n3.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000013782 260__ $$bNational Technical University of Athens, 2011
000013782 506__ $$arestricted
000013782 520__ $$2eng$$aThis paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force-displacement trajectories. The proposed neural network controller is therefore trained based on data derived from these desired forcedisplacement curves, where the optimal relation between friction force level and response amplitude is determined explicitly by simply maximizing the damping ratio of the targeted vibration mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed to determine the damper current based on the derived optimal damper force. For that reason an inverse MR damper model is also designed based on the neural network identification of the particular rotary MR damper. The performance of the proposed controller is compared to that of an optimal pure viscous damper. The top floor displacement and acceleration of the base excited shear frame structure are selected as the performance parameters of this comparison. It is found by the simulations that the proposed control design yields a reduction in the structural response compared to the viscous case.

000013782 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000013782 653__ $$aMagnetorheological damper, neural network, semi-active control.

000013782 7112_ $$aCOMPDYN 2011 - 3rd International Thematic Conference$$cIsland of Corfu (GR)$$d2011-05-25 / 2011-05-28$$gCOMPDYN2011
000013782 720__ $$aBhowmik, S.
000013782 8560_ $$ffischerc@itam.cas.cz
000013782 8564_ $$s837523$$uhttps://invenio.itam.cas.cz/record/13782/files/667.pdf$$yOriginal version of the author's contribution as presented on CD, section: MS 08 Control of Vibrations in Civil Engineering by Passive Active and Semi-Active Devices.
000013782 962__ $$r13401
000013782 980__ $$aPAPER