TJ197 : Modeling and Control of Magneto-Rheological Dampers
Thesis > Central Library of Shahrood University > Mechanical Engineering > MSc > 2010
Authors:
Mohammad Sheibani [Author], Ardeshir Karami mohammadi[Supervisor]
Abstarct: Magnetorheological (MR) dampers are tools for semi-active control which are widely being used because of their rapid response, low energy consumption, and high reliability. Automobile suspension and structural vibration control systems are among the most frequent uses of such dampers. The main challenge to the expansion of using these dampers is presenting a model capable of simulating their linear and complex hysteresis behaviors in a suitable manner. So far many different models have been presented for simulation of hysteresis of magneto-rheological dampers. Models such as Bouc-Wen’s parametric model and other non-parametric models are baxsed on sigmoid functions. Nevertheless, many of these models demonstrate differences between results of experimental tests and simulations. Also, in most models the model characterizing parameters are not functions of frequency, amplitude and current of stimulation. Thus they must be recalculated for different stimulation conditions. In this thesis three new non-parametric hysteresis models are offered for simulation of behaviors of magneto-rheological dampers. The offered models takes the excitation frequency, amplitude and current as variables and because of that it are capable of estimating the hysteresis force in different stimulation conditions with a good level of accuracy. Also, these models have the required level of flexibility for simulation of different dampers. The models completion is free of all complications observed in other models. Finally, the accuracy of simulations provided by these models were compared with experimental data and two parametric and non-parametric models.in the last chapter the effects of applying a Magnetorheological damper on a car suspension system is investigated.
Keywords:
#Magneto-Rheological Fluid and Damper #Modeling #Neural Network #Semi-active control Link
Keeping place: Central Library of Shahrood University
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