On the Control of Shaking Tables in Acceleration Mode: An Adaptive Signal Processing Framework

Abstract

This Chapter proposes a framework for the control of shaking tables on the basis of adaptive signal processing and parameter estimation methods. The applied methodology bypasses any analytical modeling scheme and treats the table as a black–box mechanical system, the output of which must replicate a predefined time–series of diverse spectral characteristics. A central feature of the proposed scheme is the operation in acceleration mode that allows a wider response spectrum to be actually implemented to the specimen. Control is achieved by realizing a two–stage procedure, at which (i) the dynamics of the shaking table are identified, including any transfer delay, and (ii) an inverse controller is adaptively estimated and placed in series before the table’s controller, aiming at filtering the reference acceleration in a way that cancels the table dynamics. Both stages, which can can be applied either on–line, or off–line, must be conducted with the specimen installed on the table. For its practical evaluation, the method is successfully applied to shaking table waveform replication tests under the installation of an approximately linear specimen of sufficiently high mass (comparable to the mass of the table) and complex geometry.