To overcome the shortcomings of the Bouc–Wen model, such as too many parameters, complex identification process, and long time consuming, the sensitivity of parameters was analyzed. A Bouc–Wen optimum model with sensitive parameters to guarantee calculating accuracy was established. First, according to the results of the magnetorheological damper’s mechanical property test, the sensitivity of Bouc–Wen model’s parameters was analyzed by the one-at-a-time method. Optimization of the Bouc–Wen model was completed. Second, the parameters of the Bouc–Wen optimum model were identified under three harmonic excitations. Compared with the original Bouc–Wen model, the differences of calculation accuracy were 0.0055, 0.0007, and 0.0070 respectively. And the convergence rate of the fitness function for parameter identification increased by 67.89%, 49.94%, and 67.24%, respectively. And the iteration time of 1000 iterations was shortened by 36.52%, 25.95%, and 64.11%, respectively. It indicates that the Bouc–Wen optimum model had higher efficiency and certain accuracy in parameter identification process. Then, the calculation accuracy of Bouc–Wen optimum model with independent and coupled mean parameters were analyzed respectively. Finally, the parameters of the Bouc–Wen optimum model and current were fitted by the least square method. The results showed that the Bouc–Wen optimum model can accurately and efficiently simulate the dynamic characteristics of magnetorheological dampers.

To study the influence of temperature and internal leakage on the performance of magnetorheological (MR) damper, a single‐rod straight‐cylinder MR damper with an inside temperature sensor is designed in this study. A unified model for MR damper is given, and a new two‐step parameters identification method is proposed to determine model parameters. The experiment, in which the damper is heated by long‐time displacement excitation, is designed to study the effect of temperature and internal leakage. The influence mechanism of temperature and internal leakage on MR damper is analyzed through theoretical derivation and experimental results in this study.

An adaptive active disturbance rejection controller is used in the current driver design of the electromagnetic coil. Extended state observer of the 1^st‐order system is adopted for disturbance observation of ADRC. The supervised recursive least squares method is proposed for real‐time parameters estimation, in which the excitation signal variance is used to trigger the parameter estimator. The experimental results demonstrate that ADRC combined with real‐time parameter estimation simplifies the parameter tuning and improves the parameter adaptive ability.