Experiments in dynamics and control

The development of enhanced sensors and experimental techniques (e.g., high-resolution laser video captures, 3D laser scanner vibrometry, image digital processing) has enabled significant advances to be made in the measurement of complicated phenomena in nonlinear mechanical systems. These developments and the wider availability of general experimental devices have sparked a rich proliferation of experimental studies. Research efforts both in academia and in industry are targeted towards different objectives such as nonlinear dynamical system approaches to data analysis and interpretation; comparisons with analytical/reducedorder model predictions; and novel nonlinear vibration control methods in a variety of fields, such as mechanics, structural engineering, fluid-structure interaction, biomechanics, acoustics, embedded and hybrid multiphysics systems. The research in the field of experimental approaches to nonlinear dynamics and control is inherently multidisciplinary and requires an integrated approach to tackle the open problems. In particular, the following areas are worth highlighting: (i) novel experimental techniques to assess and enhance understanding of dynamical phenomena; (ii) experimental observations of new and complex dynamical phenomena in the broad area of nonlinear mechanical systems and structures; (iii) extraction/identification of reduced-order models of nonlinear systems (including hysteresis, impacts, and delays) via experimental data; (iv) experimental verification and validation of motion stabilization and control by using nonlinear effects; (v) experimental investigation of energy harvesting techniques that exploit nonlinear dynamical phenomena. This has led us to co-organize a Special Issue for the Journal of Vibration and Control in the broad field of experimental dynamics and control. The contributions span the rich diversity of the mentioned research areas and document state-of-the-art approaches and phenomena including studies that focus on nonlinear phenomenology to enhance the system performance and control strategies.