Fuzzy Neural Networks Control of A Semi-active Suspension System with Dynamic Absorber

For a semi-active suspension design, an important subject is to determine the control law which can achieve good performance both in ride and handling performance. Because of its superiority in non-linear control systems and capability of learning on-line, the fuzzy neural networks (FNNs) control scheme is proposed in this paper for a semi-active suspension system with dynamic absorber. The quarter vehicle model is described by a nonlinear system with three DOF subject to irregular excitation from a road surface and FNNs control scheme is employed. The on-line learning of FNNs to optimize fuzzy inference system is presented. Four kinds of methods, including passive suspension respectively with and without dynamic absorber, semi-active suspension respectively using fuzzy control and FNNs control, are investigated by computer simulation and comparison is made. It is indicated that the semi-active suspension system employing the FNNs control strategy proposed in this paper is more effective in improving the performance of vehicle by comparing with other methods and also shown how the addition of a dynamic absorber reduces the excessive vibration of the wheel mass by a great amount.