Combined fuzzy-PID control for air suspension of car
Zhu Xing-hua
Abstract
Zhu Xing-hua
Abstract
One quarter air suspension model and the white-noise road model are established by taking the air suspension system of car as a study case in it,the dynamic integration between the fuzzy control theory and PID control strategy is applied to active control of the air suspension system.At the same time simulation study is carried out by utilizing MATLAB/Simulink,which results shows that,compared with the traditional PID and the fuzzy control,the control of the semi-active air suspension may reduce the sprung mass acceleration and suspension action itinerary with better robustness advantages under the combined fuzzy PID control strategy,and the ride comfort of the car is improved to a certain degree.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
One quarter air suspension model and the white-noise road model are established by taking the air suspension system of car as a study case in it,the dynamic integration between the fuzzy control theory and PID control strategy is applied to active control of the air suspension system.At the same time simulation study is carried out by utilizing MATLAB/Simulink,which results shows that,compared with the traditional PID and the fuzzy control,the control of the semi-active air suspension may reduce the sprung mass acceleration and suspension action itinerary with better robustness advantages under the combined fuzzy PID control strategy,and the ride comfort of the car is improved to a certain degree.
Key concepts: Sprung mass, PID controller, Air suspension, Control theory (sociology), Suspension (topology), MATLAB, Engineering, Fuzzy control system