In view of the problems of high nonlinearity and multiple parameters in existing models of magnetorheological elastomer (MRE) base isolator, this paper proposes an improved Dahl model and an enhanced genetic algorithm (GA) for model parameter identification. In this model, the Dahl hysteresis operator is employed to depict the Coulomb force to avoid the estimation of many parameters and this model can perfectly capture the hysteretic behavior of the MRE base isolator at both small and large displacements. To improve the searching efficiency of identification process, adaptive crossover and mutation operators are introduced into the GA to avoid the algorithm falling into the local optimum, achieving faster convergence rate for optimal solutions. Furthermore, an appropriate stopping criterion is designed to reduce the calculation cost. Testing data from a practical MRE base isolator are utilized to validate the proposed algorithm with satisfactory parameter identification results.
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