Estimating robust optimum parameters of tuned mass dampers using multi-objective genetic algorithms

Tuned mass dampers (TMD) are a well-known control device widely used to control the vibratory problem originated by the pedestrian action on footbridges. The main purpose of this study is the robust multi-objective optimization design of a TMD using genetic algorithms to control the structural vibrations of a footbridge due to the pedestrian action. The performance of the TMD has been improved designing optimally its parameters, including, mass, stiffness and damping ratio using multi-objective genetic algorithms. Moreover, in order to take into account the uncertainties existing in the system, a robust design optimization procedure has been performed. As an example, a slender steel footbridge, modelled by 3-D frame elements, is used to assess numerically the performance and accuracy of the proposed method. The pedestrian action has been simulated by an equivalent harmonic force. The proposed approach is compared with the classical Den Hartog's proposal. This comparison shows that this approach is more effective than the classical reported method and more feasible due to the smaller TMD parameters.