On the Application of Support Vector Method for Predicting the Current Response of MR Dampers Control Circuit

Abstract

Magnetorheological (MR) dampers are controlled energy-dissipating devices utilizing smart fluids. They operate in a fast and valveless manner by taking advantage of the rheological properties of MR fluids. The magnitude of the response of MR fluids, when subjected to magnetic fields, is of sufficient magnitude to employ them in various applications, namely, vibration damping, energy absorption, exoskeletons, etc. At the same time, predicting their response to arbitrary mechanical and electrical inputs is still a research challenge. Due to the non-linearities involved in material properties or the design of the solenoid used for activating the fluid modeling the relationships between the control circuit and the material’s response is complex. Modeling studies can be classified into two categories. The parametric approach requires the knowledge of the internal material’s properties and takes advantage of physics formulas to infer the I/O relationships present in the damper. For comparison, the non-parametric approach harnesses various data mapping techniques to describe the device’s behavior. While the latter is more suited for design studies, the former seems ideal for control algorithm prototyping and the like. In this study, based on the so-called Support Vector Method (SVM), the authors develop a non-parametric model of the control circuit of an exemplary rotary MR damper. To the best of the author’s knowledge, it is the first attempt at an SVM application for MR dampers’ control circuit modeling. Using the acquired experimental data, the I/O relationships are inferred using the SVM algorithm, and its performance is verified across a wide range of excitation frequencies. The obtained results are satisfactory, and the current response of the MR damper is well-predicted. The model performance shows the potential for incorporating it into model-based prototyping and designing of MR control systems.