Abstract
In this work, an adaptive path tracking control approach for autonomous vehicle systems is proposed in presence of dynamical uncertainties, input saturation, and actuator failures. The unknown system characteristics are described as a coefficient matrix, which is estimated by utilizing an iterative learning algorithm. Furthermore, a fault-tolerant learning scheme is developed to deal with potential actuator failures caused by the vehicle loss or accidents. In addition, a saturation compensator is used to mitigate the negative effects of the actuator saturation. The adaptive path tracking controller is then designed by adopting the adaptive backstepping approach. The convergence of the proposed control method is analyzed by applying the composite energy function methodology, and its efficacy is demonstrated by using numerical simulation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
