Abstract
This paper presents a parameter recognition based on particle swarm optimization algorithm for Bouc-wen model. In this paper, the parameters of Bouc-wen model were identified by utilizing the experimental data of mechanical properties of MR dampers. Combined with particle swarm optimization (PSO), the identification accuracy of PSO was improved by narrowing the range of parameters, and then the parameters of the model were identified. The results show that the identified model parameters can accurately match the experimental results with the simulation results, and can describe the hysteresis characteristics of damping force well.
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Yang, Y., Ding, Y., Zhu, S. (2020). Parameter Identification of MR Damper Model Based on Particle Swarm Optimization. In: Wang, R., Chen, Z., Zhang, W., Zhu, Q. (eds) Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019). Lecture Notes in Electrical Engineering, vol 582. Springer, Singapore. https://doi.org/10.1007/978-981-15-0474-7_52
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DOI: https://doi.org/10.1007/978-981-15-0474-7_52
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