Extended Kalman Filter

In the context of civil and industrial structures, structural control and damage de-tection have recently become an area of great interest. The safety of a structure is always the most important issue for structural engineers, and to achieve this goal, the discipline of Structural Health Monitoring (SHM) was introduced. SHM records real-time information concerning structural conditions and performances. In order to evaluate the health conditions of structures, identifying the structural parameters is needed. Research activities of this area are increasing due to the availability of computation and wireless technologies. The objective of this thesis is to evaluate the tracking ability of the Kalman filter for identifying civil structural parameters based on measured vibration data which usually are earthquake accelerations. For linear elastic structures, the ordi-nary Kalman filter was used, but for nonlinear elastic structures, we implemented the extended Kalman filter. For simulating damage occurrence in structures, a sud-den change of stiffness was introduced, and an adaptive extended Kalman filter wa