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A semi-active controller-based Fuzzy logic for a suspension system with magnetorheological (MR) dampers is presented and evaluated. An Inverse Fuzzy Model (IFM) is constructed to replicate the inverse dynamics of the MR damper. The typical control strategies are Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) controllers with a Clipped optimal control algorithm, while inherent time-delay and non-linear properties of MR damper lie in these strategies. LQR part of LQG controller is also designed to produce the optimal control force. After that the LQG controller and the IFM models are linked to control strategy. The effectiveness of the IFM is illustrated and verified using simulated responses of a full-car model. The results demonstrate that by using the IFM model, the MR damper force can be commanded to follow closely the desirable optimal control force. The membership functions of IFM tuned by the results of Clipped optimal strategy. The results also show that the control system is effective and achieves better performance and less control effort than the optimal in improving the service life of the suspension system and the ride comfort of the car.

Fuzzy Inverse Model of Magnetorheological Dampers for Semi-Active Vibration Control of an Eleven-Degrees of Freedom Suspension System