System identification can be formulated as a multimodal optimization problem with high dimension.The original particle swarm optimization（PSO） usually suffers from premature convergence tending to get stuck to local optima and low solution precision while solving these complex multimodal problems.In order to solve this problem

a quantum particle swarm optimization（QPSO） method was utilized to estimate parameters of structural systems.The potentialities of QPSO are its simple structure

less design parameters

easy use

fast convergence

premature convergence discouraged and global optimal searching property.The effectiveness of the proposed method was evaluated through the numerical simulations and an application to a real building.The effectiveness of the proposed method is evaluated through the numerical analysis and an application to a real building under conditions including limited measurement data

noise polluted signals

and no prior knowledge of mass

damping

or stiffness.