Abstract
Active suspension plays a pivotal role in modern vehicles. In this
paper, an adaptive PID controller of active suspension systems based on
RBF neural network (RBF-NN) is developed. A quarter-car suspension
system with two degrees of freedom is demonstrated. The values of
proportional, integral, and derivate components are obtained by using
Ziegler-Nichols(Z-N) tuning method and RBF-NN methods. The suspension
system is perturbed using the sine function. Simulated in the Simulink
environment is the quarter-car model. Passive suspension systems,
adaptive PID controller utilizing the Z-N tuning approach, and adaptive
PID based on the RBF-NN method for active suspension systems are
compared. The active suspension with PID control based on the RBF-NN
outperformed the active suspension with PID control utilizing the Z-N
tuning approach and passive suspension, according to simulation data.
The comparison demonstrates the proposed control method’s superior
features