This paper presents a feedback gain adaptive path tracking algorithm on autonomous mobility that is based on disturbance reconstruction with a sliding mode observer(SMO). In the design of the path tracking controller vehicle error dynamics, the desire...
This paper presents a feedback gain adaptive path tracking algorithm on autonomous mobility that is based on disturbance reconstruction with a sliding mode observer(SMO). In the design of the path tracking controller vehicle error dynamics, the desired yaw rate is generally required. The simple kinematics-based error dynamics was used, while the disturbance, including the desired yaw rate, was reconstructed by an SMO under a finite-time stability condition in real-time.
The feedback gains in determining the steering control input adaptively are computed by using the desired eigenvalue and vehicle longitudinal velocity. Finally, to obtain a reasonable performance evaluation, waypoint-based curved path scenarios were examined under two velocity conditions in Matlab/Simulink and CarMaker software environment.