Enhanced variable universe fuzzy PID control of the active suspension based on expansion factor parameters adaption and genetic algorithm

Abstract The optimal value of the expansion factor and quantization parameters is key to determine performance variable domain fuzzy proportion-integral-derivative (PID) controller. In view problem that relevant are fixed, difficult cannot be adjusted adaptively in traditional PID control, a kind enhanced control (EVUFP) proposed improve ride comfort vehicles. First, based on an adaptive controller constructed adjust real time. Then genetic algorithm used optimize scale seek parameters. And obtained substituted into Simulink model realize design EVUFP simulation experiment results under different working conditions show strategy can reduce root mean square (RMS) values body acceleration, suspension dynamic deflection tire load by more than 54%, 50% 23%, respectively, vehicles, provide new idea for development active suspensions.