Data-Driven Control of Disturbance Compensator/PI Controller for Yaw-rate Control of Autonomous Driving

Abstract

For realizing desired control performances, data-driven tunings called as Fictitious reference iterative tuning (FRIT) were proposed. If FRIT can be applied to vehicle yaw-rate control of autonomous driving, the desired control performance can be realized. However, the conventional FRIT may not realize desired control performances because of slip-angle properties. To solve this problem, we extend FRIT method so as to cancel influence of the vehicle slip-angle. The validity of proposed method is verified through multi-body vehicle simulator.