Model identification of a large-scale magnetorheological fluid damper

Abstract

In recent years there has been an increasing interest in magnetorheological (MR) dampers and their applications to civil engineering structures. In particular they have been used as semi-active control devices for the mitigation of vibration due to external dynamic loads. These devices are highly nonlinear, and thus accurate models of them are important for effective simulation and control system design. A hysteretic model based on the normalized Bouc–Wen model is proposed in this paper to test its effectiveness in a large-scale MR fluid damper. A methodology for identification is proposed, and the obtained model is tested and validated experimentally.

Parameter Identification of Large-Scale Magnetorheological Dampers in a Benchmark Building

“…The parameter identification in [17] departs from the next shear-mode model: where κ x > 0, κ w > 0, ρ > 0, σ > 1/2, and n ≥ 1. For parameter identification, a T -periodic inputẋ(t) (see Figure 14) is applied to the Bouc-Wen system under constant voltage v. It has been proved [7] that the output force of the Bouc-Wen model goes asymptotically to a periodic steady-state so that a limit cycle is obtained.…”

“…In this regard, a new parameter identification algorithm has been proposed in [7, p. 38], which is based on a physical understanding of the device along with a black box description. Rodríguez et al [17] used this methodology for a large-scale MR damper. The method is based on applying a periodic input velocityẋ(t) at a constant voltage coil v and observing the periodic steadystate force response of the MR damper.…”

“…The proposed algorithm will be divided in two steps: (a) the estimation of the value of κ x and (b) the estimation of the rest of the parameters based on the identification algorithm in [17].…”

“…we can follow basically the same idea as in [17]. The details of this method are omitted here but can be found in the Appendix.…”

“…To cope with this drawback, a modified step was proposed by Rodríguez et al [16] and tested in a small-scale MR damper. When the identification is applied to a large-scale MR damper, the parameter identification errors increase [17]. The aim of this paper is to improve the accuracy of the identification algorithm.…”