Abstract

The performance of a damping-controllable dynamic damper was investigated with an adaptive neural net control system. The damping controllability of the dynamic damper was accomplished by introducing the Electro-Rheological (ER) fluid, which is known as one of the highly functional materials and whose apparent viscosity can be varied in accordance with applied electric field strength in a wide range as well as in a short time. As a control system for the present dynamic damper, an adaptive neural net control system was developed ; it was composed of a forward model network and a controller network. With the proposed neural net control system, the damping-controllable dynamic damper can be tuned by itself even if response of a structure shows nonlinearity to input disturbances or varies its own dynamic characteristic. Moreover, the vibration amplitude corresponding to several natural frequencies can be reduced with only a single dynamic damper. Numerical and experimental investigations were performed, and the results shows the superiority of the present adaptive vibration control system.

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