Parameter Identification and Simulation of the Noise-Involved Hysteretic Model Using Improved Genetic Algorithm

Hysteresis is a specific character of a wide range of physical systems and devices, such as electromagnetic fields, mechanical stress-strain elements, and electronic relay circuits. The extended Bouc-Wen model is one of the most widely accepted phenomenological models of hysteresis in mechanics. However the multi parameters have plagued its further application because the capability of computer and algorithm available currently can not meet the need completely. Thus to exploit an efficient and accurate parallel algorithm is very essential and significant. This paper is committed to propose an improved genetic algorithm (GA) so as to identify the parameter of the Bouc-Wen model effectively. Finally a large amount of noise-involved data is employed to verify the proposed approach is very effective and accurate.