A pneumatic muscle is a cheap, clean, and high-power active actuator. However, it is difficult
to control due to its inherent nonlinearity and time-varying characteristics. This paper presents a
pneumatic muscle active suspension system (PM-ASS) for vehicles and uses an experimental study to
analyze its stability and accuracy in terms of reducing vibration. In the PM-ASS, the pneumatic muscle
actuator is designed in parallel with two MacPherson struts to provide a vertical force between the
chassis and the wheel. This geometric arrangement allows the PM-ASS to produce the maximum force
to counter road vibration and make the MacPherson struts generate significant improvement. In terms
of the controller design, this paper uses an adaptive Fourier neural network sliding-mode controller
with H∞ tracking performance for the PM-ASS, which confronts nonlinearities and time-varying
characteristics. A state-predictor is used to predict the output error and to provide the predictions for
the controller. Experiments with a rough concave-convex road and a two-bump excitation road use
a quarter-car test rig to verify the practical feasibility of the PM-ASS, and the results show that the
PM-ASS gives an improvement the ride comfort.
