Multiobjective Cuckoo Search Algorithm Based on Duffing´s Oscillator Applied to Jiles-Atherton Vector Hysteresis Parameters Estimation

The parameter identification of hysteresis models is a fundamental task for correct hysteretic material simulation. In vector models, as the Jiles-Atherton (J-A) vector model, the parameter determination increases in complexity since one must solve a nonlinear system with a relative large number of variables. In these cases, fitting methods one of the most attractive solution. In this study, an improved multiobjective cuckoo search (IMCS) is introduced for the J-A parameters determination. The proposed IMCS based on the Duffing´s oscillator to step size tuning is verified using data from a rotational single sheet tester in two-dimensional version. Numerical comparisons of IMCS with results using a multiobjective cuckoo search demonstrated that the performance of the IMCS is promising in parameters estimation. Furthermore, the proposed IMCS method can be easily extended to solve a wide range of multiobjective optimization problems.