Finite element model updating methodologies allow the identification of structures by improving the accuracy of an initial finite element model considering data acquired from a vibration test. Usually, numerical predictions and experimental results disagree thus requiring an updated model that best reproduces the dynamic behavior of the actual structure. Several updating methodologies have been developed in the last years such as the modal-based and response-based ones, which minimize the difference between the measured and predicted modal parameters and Frequency Response Functions, respectively. This thesis investigates a response-based method which iteratively minimizes a residual vector defined on the correlation functions between the Frequency Response Functions, which are directly available from experimental tests, to identify the mismodeled regions of a numerical model and improve the correlation with its experimental counterpart. The minimization problem is generally solved by means of the weighted least-squares approach and starting from a reference formulation available in literature, some enhancements are proposed, validated numerically, and extended to real experimental data using simple structures such as beams and plates. Finally, the proposed methodology is applied to identify the physical properties of a reduced-scale helicopter blade model that incorporates a semi-active device for vibration control, named Smart Spring. As a further study, the effectiveness of this device to reduce vibration is analytically verified through the development of its mathematical model in the frequency domain that makes use of an open-loop control law. Moreover, the capability of the Smart Spring to modulate the structural properties of a system and alter its dynamic behavior, thus acting as a semi-active device, is experimentally assessed through vibration tests performed at different operative working conditions of the device.