6533b853fe1ef96bd12aca82

RESEARCH PRODUCT

Neural network-based models for a vibration suppression system equipped with MR brake

Witold PawlusHamid Reza Karimi

subject

VibrationModeling and simulationArtificial neural networkMathematical modelControl theoryComputer scienceMagnetorheological fluidBrakeVibration controlSimulationDamper

description

This paper is devoted to the modeling and simulation of a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system. The analysis of the Bouc-Wen and Dahl mathematical models of MR damper is presented. Influence of their parameters on the response is explored. Subsequently, by using the neural networks, the parameters characterizing each model are estimated. This makes it possible to perform the comparative analysis of the suggested damper models responses with the measured experimental results. The novelty of the presented methodology is the application of artificial intelligence methods to estimate model parameters of a MR brake utilized in a SAS system. The results of this approach have a strong potential to be successfully utilized in the area of model-based control of semi-active vibration suppression systems.

yearjournalcountryeditionlanguage
2012-09-012012 6th IEEE INTERNATIONAL CONFERENCE INTELLIGENT SYSTEMS
https://doi.org/10.1109/is.2012.6335156