Research on Structure Design and Control Method of Magnetorheological Suspension Based on Improved Fruit Fly Optimization Algorithm

To reduce engine vibration, a semi-active controlled magnetorheological suspension is designed. First, the magnetic circuit of new simulated. Furthermore, non-parametric forward and inverse dynamic models with Elman neural network are established, where modeling results accuracy analyzed. Second, according to characteristics vibration control suspension, an improved fruit fly optimized proportional-integral-differential (PID) controller proposed. Compared original PID particle swarm optimization controller, strategies based on proposed methods simulated by MATLAB. Then, experiment carried out under different strategies. The simulation show that algorithm has advantages short adjustment time fast response.