Suspension System Control with Fuzzy Logic
DOI:
https://doi.org/10.22385/jctecs.v6i0.73Keywords:
Active suspension, Fuzzy logic controller, One-quarter-car model, Vehicle.Abstract
In this paper, fuzzy logic is used to control active suspension of one-quarter car model. The main role of a car suspension system is to improve the ride comfort and to better the handling property. It usually consists of a spring and a damper to improve the properties of suspension system. The fuzzy logic method is one of the most active research and developments areas on artificial and intelligence at the present time, particularly in the automobile industry. One quarter of car if modeled by springs, masses, dampers and force actuator and the state space equations are derived by lagrangian method. The ride comfort is improved by means of the reduction of the body acceleration caused by the car body when road disturbance from uneven road surfaces, pavement point etc. act on the tires of running car. Here, a logic fuzzy controller is designed in which, the number of rule bases are reduced in comparison with some traditional one which have been introduced in other papers. At the end, a comparison of active suspension fuzzy control and traditional passive suspension is shown using MATLAB simulations. Results show that, active suspension improves the ride comfort by reducing acceleration, compared with the performance of passive suspension.
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References
T. Yoshimura., , I. Teramura, “ Active suspension control of one wheel car model using single input rule models fuzzy reasoning and a disturbance observer “ , Journal of Zhejiang University SCIENCE, ISSN: 1009-3095, page: 251-256, 2005.
A. Stříbrský, K. Hyniová, J. Honců, A. Kruczek, “ Using fuzzy logic to control active suspension system of one-half-car model “, Ročník 8 pp. 223-227, 2003.
Á. HYNIOV, K., A.STŘÍBRSKÝ, and J. HONCŮ, ” Fuzzy Control of Mechanical Vibrating Systems ”, International Carpatian Control Conference ICCC 2001, pp. 393-398, Krytica, Poland, 2001.
K.Tanaka, , “ An introduction to fuzzy logic for practical applications “, Springer, 1997
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