COMPARATIVE STUDY OF OPTIMIZATION ALGORITHMS FOR PARAMETER IDENTIFICATION OF THE SIGMOID MODEL IN MR DAMPER
Sigmoid, Fminsearch, Differential Evolution MR damper
This study focuses on the parameter identification of a commercial magnetorheological (MR) damper. The nonlinear behavior of the MR damper was modeled using the numerically parameterized sigmoid model proposed by Wang, which utilized experimental dynamic behavior of a commercial MR damper and applies a method to fit symmetric and asymmetric sigmoid functions using experimental data. Two optimization methods, namely the Nelder-Mead simplex search method (fminsearch) and the differential evolution (DE), were proposed as minimization algorithms. The performance of the optimization methods was compared. The dependency of frequency excitation, piston displacement, current applied in the coil and the operating temperature of the MR damper were also evaluated. The validation of the model parameter was achieved by comparing experimental results with predicted values. The results show that the proposed methodology is effective in identifying the parameter of the MR damper and can be used to improve the performance of the suspension system.