A new adaptive fuzzy-hybrid control strategy of semi-active suspension with magneto-rheological damper
This paper presents the design and analysis of a new adaptive fuzzy (AF) logic and hybrid (skyhook plus groundhook) control technique applied to a semi-active suspension system of a quarter car mode. The hybrid control is applied because of its very good performance in ride comfort and road handling. Meanwhile, Fuzzy adaptive system is suitable for analysis of stability with non-linear performances. The adaptive fuzzy algorithm is used to approximate the estimated mass of the variable damping in the Hybrid loop. This model is adopting a Takagi-Sugeno configuration with a back propagation learning method typically used in a neural network configuration, which uses a product inference engine, singleton fuzzifier, centre average defuzzifier, and Gaussian membership function. Numerical simulations were conducted based on Simulink/Matlab using Fuzzy Logic Toolbox. It is found that the semi-active suspension system with the proposed adaptive fuzzy-hybrid yields superior performance compared to both the Hybrid and the Passive counterparts.
Nugroho, P. W., Du, H., Li, W. H. & Alici, G. (2012). A new adaptive fuzzy-hybrid control strategy of semi-active suspension with magneto-rheological damper. In Y. Gu & S. Saha (Eds.), 4th International Conference on Computational Methods (pp. 1-9).