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A fuzzy logic controller (FLC) is designed and implemented in real time on a Toyota Celica test vehicle to achieve control of the lateral motion of the vehicle. The structure of FLC is modularized as feedback, preview, and gain scheduling rule bases. The parameters of FLC are tuned manually using information from the characteristics of human driving operation and existing controllers. Three feedback FLCs with different feedback variables are designed. A fuzzy preview rule base is developed to utilize preview information regarding the upcoming radii of curvature. Also, a gain scheduling rule base is designed to choose the appropriate controller based on the velocity of the vehicle. These fuzzy logic control strategies are implemented on the test vehicle which follows automatically a multiple curved track using discrete magnetic markers on the roadway and magnetometers on the vehicle as a lateral error reference/sensing system. The experimental test results of the FLCs, which are designed based on an implicit model of the vehicle, are shown, and a comparison is made to similar tests conducted using the frequency shaped LQ controller as well as PID controller, both are designed based on an explicit model of the vehicle.>
Hessburg et al. (Mon,) studied this question.