Experimental modeling of magneto-rheological damper and PID neural network controller design

MR fluid is a material that responds to an applied magnetic field with a significant change in its rheological behavior. With the outstanding features of MR fluid, MR dampers are a new class of devices that more suitable for the requirements of automotive applications, including having very low power requirements. Using a large number of test data, a phenomenological model based on the Bouc-Wen hysteresis model was adopted to predict both the force-displacement behavior and the complex nonlinear force-velocity response. For the purpose of developing semi-active controller, the theory of PID neural network control is adopted here to identify and control the semi-active suspension systems. The result showed that, under the control of the PID neural network controller, the MR damper could reduce the acceleration in varied ride conditions. The primary goal of this paper is to create a reliable, effective and safe semi-active suspension controller that improves the ride comfort as well as safety of automotive performance.