TY - JOUR
T1 - A new hybrid model for MR elastomer device and parameter identification based on improved FOA
AU - Yu, Y.
AU - Yousefi, A.M.
AU - Yi, K.
AU - Li, J.
AU - Wang, W.
AU - Zhou, X.
PY - 2021
Y1 - 2021
N2 - A new hysteresis model based on curve fitting method is presented in this work to portray the greatly nonlinear and hysteretic relationships between shear force and displacement responses of the magnetorheological (MR) elastomer base isolator. Compared with classical hysteresis models such as Bouc-Wen or LuGre friction model, the proposed model combines the hyperbolic sine function and Gaussian function to model the hysteretic loops of the device responses, contributing to a great decline of model parameters. Then, an improved fruit fly optimization algorithm (FOA) is proposed to optimize the model parameters, in which a self-adaptive step is employed rather than the fixed step to balance the global and local optimum search abilities of algorithm. Finally, the experimental results of the device under both harmonic and random excitations are used to verify the performance of the proposed hybrid model and parameter identification algorithm with the satisfactory results.
AB - A new hysteresis model based on curve fitting method is presented in this work to portray the greatly nonlinear and hysteretic relationships between shear force and displacement responses of the magnetorheological (MR) elastomer base isolator. Compared with classical hysteresis models such as Bouc-Wen or LuGre friction model, the proposed model combines the hyperbolic sine function and Gaussian function to model the hysteretic loops of the device responses, contributing to a great decline of model parameters. Then, an improved fruit fly optimization algorithm (FOA) is proposed to optimize the model parameters, in which a self-adaptive step is employed rather than the fixed step to balance the global and local optimum search abilities of algorithm. Finally, the experimental results of the device under both harmonic and random excitations are used to verify the performance of the proposed hybrid model and parameter identification algorithm with the satisfactory results.
UR - https://hdl.handle.net/1959.7/uws:66897
U2 - 10.12989/sss.2021.28.5.617
DO - 10.12989/sss.2021.28.5.617
M3 - Article
SN - 1738-1991
SN - 1738-1584
VL - 28
SP - 617
EP - 629
JO - Smart Structures and Systems
JF - Smart Structures and Systems
IS - 5
ER -