Fuzzy logic controlling motorbikes antiskid

Active antiskid systems for high performance motorbikes are difficult to implement due to the necessity to combine performance, equilibrium, handling and safety. In order to design and optimize a fuzzy controlled antiskid system for motorbikes, a fuzzy model of the pilot was applied to a lumped-mass model of the motorcycle (two different models have been considered). The fuzzy pilot acts on the steering angle to control trajectory, yaw angle, yaw velocity and roll angle. Throttle position vs. time curve, gear and an adherence model between tyre and road are given as input. The fuzzy pilot is implemented with Matlab/Simulink, and simply tries to keep equilibrium. Only measurable inputs were given as input variables of the antiskid fuzzy controller. The output is the percent reduction in throttle position. The motorcycle-fuzzy-pilot model proved to be quite accurate. Motorcycle maximum velocity resulted higher than the real one due to the simplifying hypothesis. In curves, the fuzzy pilot is less efficient than the real pilot. In fact, there was a low frequency oscillation around the optimum steering angle. This fuzzy controlled antiskid proved to work quite well since equilibrium is attained also in critical situations where the motorcycle-fuzzy-pilot model alone fails to keep equilibrium.