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Trajectory Tracking of Autonomous Vehicle That Uses State Feedback Linearization with Ackerman Method and Observer Feedback
Hasan H.
2022 5th International Seminar on Research of Information Technology and Intelligent Systems Isriti 2022
Abstract
In recent years, research about vehicle trajectory tracking has become one of the significant fields in autonomous vehicle control development, especially with the presence of some new control technics that can complete the autonomous vehicle technology. The research aim is to develop controllers applied to control the autonomous vehicle that navigates along a predefined path that considers two unique scenarios in real-world driving. This paper contains two parts that define the method of the research. In the first part of the paper, the kinematic model of the vehicle is developed based on some references from previous research, and then a nonlinear controller from the class of state feedback linearization using the Ackerman method is applied to this nonlinear vehicle model to have a new control law that efficient enough in controlling such as model. In the second part of the paper, an observer is added to the state feedback linearization system to generate a steering angle that is a nonlinear vehicle model and to achieve stable tracking performance with minimum lateral error. The simulation results show that the control low can achieve stability, and the vehicle model has a good performance while tracking the predefined trajectory. However, some efforts are still needed to improve the performance of the vehicle system. Therefore, applying a new control method, such as model predictive control combined with a deep learning algorithm, will be preferable in this system.