APPLICATION OF HYBRID GENETIC ALGORITHM TO STRUCTURAL DYNAMIC INVERSION

In this paper, the structural parameter identification and the load identification of inverse analysis are studied. The resultant nonlinear global optimization problem is solved using a hybrid genetic algorithm in which the BFGS algorithm is chosen for local search. With no information of input excitation forces, a calculation strategy of decomposition inversion is presented, which improves the robustness and convergence rate of the hybrid genetic algorithm. Numerical simulation studies are performed. For verification purpose, both the noise-free and noise-included output responses are considered. Results show that the proposed method is efficient not only for structural parameter identification but also for load identification in inverse analysis.