Parameter identification of Bouc-Wen model for MR damper by parameter sensitivity analysis and modified PSO algorithm

Abstract

To solve the problems of the Bouc-Wen model with multi-identification parameters, low accuracy, complex methods, and difficulty in implement, this study proposes a new way for parameter identification of the Bouc-Wen model of the magnetorheological (MR) damper by parameter sensitivity analysis and modified PSO algorithm. The one-at-a-time method (OAT) of local sensitivity analysis is utilized to analyze the unknown parameters in the Bouc-Wen model to complete the model simplification. Then, the modified PSO algorithm is used to identify the parameters of the simplified Bouc-Wen model. Finally, with the relationship between the currents and identified parameters, a Bouc-Wen model for current control is constructed by the curve fitting method. The results confirm that the parameter identification efficiency achieved via the parameter sensitivity analysis is improved by 50% by reducing the parameters of the Bouc-Wen model from 8 to 4. Then, compared with the standard PSO (SPSO) algorithm, the modified one is accurate and stable, and the convergence speed is increased by 17.65% on average. At last, compared with the test data under three different sinusoidal excitations, the model’s accuracy is 89.11%, 92.56%, and 87.45%, respectively. The method proposed in this research can rapidly and accurately identify the Bouc-Wen model and lays a theoretical foundation for applying the MR damper model in vibration control.