Abstract: The damper, which is a strong nonlinear hysteretic system, is hard to be considered as a easy mathematical model. In order to solve this problem, the Bouc-wen model is applied to build a model to describe the characteristic of damper. The Bouc-wen model has been widely adopted to describe the responses of hysteretic materials and structures to applied force. Firstly, to determine the nonlineaer characteristic of damper, the curves of hysteretic characteristic are obtained through the physical tests with different frequencies and amplitudes. Using the data, the parameters of Bouc-wen model could be identified. To obtain the parameters, two different algorithms, genetic algorithm and neural network, are used to identified the parameters respectively. Comparing genetic algorithm and neural network, the simulation results show that neural network is able to achieve a smaller approximation error, and more efficint than genetic algorithm.

Key words: Damper, Radial RBF, Parameter identification, Bouc-wen model, Hysteretic