Robust Model Predictive Control for Autonomous Vehicles/Self Driving Cars
This work addresses the challenge of robust steering control for autonomous vehicles, but it appears incremental as it builds on existing MPC methods with specific tuning and linearization techniques.
The paper tackles the problem of controlling front steering in autonomous vehicles by proposing a robust Model Predictive Control (MPC) approach, which uses weight tuning and successive on-line linearization of a nonlinear vehicle model to track position and velocity errors, with results discussed in terms of accuracy and computational load.
A robust Model Predictive Control (MPC) approach for controlling front steering of an autonomous vehicle is presented in this paper. We present various approaches to increase the robustness of model predictive control by using weight tuning, a successive on-line linearization of a nonlinear vehicle model to track position error and successive on-line linearization to track velocity error. Results of the effectiveness of each method in terms of accuracy and computational load are discussed.