Substructure identification is a structural health monitoring technique that identifies a reduced order model of structural behavior using local vibration measurements. Previous research by the authors on this inherently decentralized technique has shown that substructure identification can detect and localize stiffness changes in a shear building. However, identification performance varies from story to story, with a few not satisfactorily identified. To overcome this limitation, Zhang and Johnson (2012c) showed how to use a structural control device to temporarily change the dynamics of the structure to improve identification performance. However, this method assumes full state feedback which is not achievable in full-scale implementations. This paper investigates structural control using limited sensor measurements to improve substructure identification. A 12-ft., four-story, single-bay, steel structure model subject to low levels of ground motion is used as the test-bed for numerical simulations. Different combinations of acceleration sensor locations are compared to understand the performance tradeoffs.
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