Structural health monitoring (SHM) is the process of monitoring structural health and identifying damage existence, severity and location. Clear needs for SHM exist for various types of civil structures; e.g., approximately 25% of U.S. bridges are rated as deficient and require significant expenditures to rebuild or replace them (FHWA, 2002). Yet, the dominant method for monitoring the health of civil structures is manual visual inspection. Global vibration-based SHM techniques have been studied, but no approach has been well established and accepted due to limitations of ambient excitation for most civil structures and the small sensitivity of global vibration characteristics to damage. One approach that may alleviate some of the SHM difficulties for civil structures is using variable stiffness and damping devices (VSDDs) — controllable passive devices that received significant study for vibration mitigation — to improve damage estimates. In addition to providing near optimal structural control strategies for vibration mitigation, these low-power and fail-safe devices can provide parametric changes to increase global vibration measurement sensitivity for SHM. This report proposes using VSDDs in structures to improve SHM, and demonstrates the benefits analytically and experimentally in contrast with conventional passive structures. A 2DOF bridge structure model and two shear building models (2DOF and 6DOF), are used as test beds to study the VSDD approach analytically in the context of an iterative parametric frequency domain identification. Using data from multiple VSDD configurations, and using multiple channels of data, a least-squares error formulation is used to estimate unknown structural parameters. The improvements in identification are quite effective when adding high effective levels of stiffness or damping to a structural system, though the resulting VSDD forces are small due to the low levels of ambient excitation. The VSDD approach is also studied using the Eigenvalue Realization Algorithm. In the experimental part of this study, a 2DOF shear building structure is excited using a small shaking table and the building parameters are identified. Results show that using VSDDs in identification gives parameter estimates that have more accurate means and smaller variations than the conventional structure approach.