This thesis presents a contribution to the improvement of modeling and control methodologies for smart structures. It is focused on comfort-compromising, sound- and vibration-related problems, which can be successfully handled by the concepts developed within the interdisciplinary field of adaptronics.
As far as modeling of smart structures is concerned, it is advocated in this thesis to employ theoretical modeling to gather an understanding of the fundamental system properties and of the characteristics that are relevant for control design. Theoretical modeling of a generic smart structure with electromechanical as well as mechanical-acoustical coupling is illustrated at the beginning of this thesis. However, pure theoretical modeling of complex systems generally lacks sufficient accuracy for subsequent control design. For that reason, data-driven modeling is one of the key aspects of this work. A modeling procedure is developed that is capable of identifying models for linear time-invariant systems with many resonances from measurement data along with theirassociated model uncertainty. A minimum of prior assumptions is needed.
Based on these models and their uncertainty descriptions, a straightforward yet powerful design methodology for multi-input multi-output active vibration control is presented. The resulting control design employs the well-developed machinery ofH2 optimal control, and the resulting control loops are robustly stable with respect to the a-priori identified model uncertainty. This robust optimal design methodology for multi-input multi-output controllers offers both better performance and more degrees of freedom compared to the dominating design of single-input single-output controllers for active vibration control. […]