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

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