Internal Model-Based Robust Path-Following Control for Autonomous Vehicles
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Adorján Kovács , István Vajk |
Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics , Budapest University of Technology and Economics |
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ABSTRACT |
The paper presents a new internal model control (IMC) based control technique for lateral trajectory tracking of autonomous
vehicles. The controller’s proposed structure employs a robust, fault-tolerant nonlinear internal servo control with optimal
reference generation concerning vehicle yaw stability and physical limitations. The presented inscription of the reference
generation creates a convex optimization task that can be used in real-time applications. Improvements in yaw-rate stability
of vehicle motion control are fi rst shown through simulation results performed in a Simulink environment. The controller
structure was also implemented in a real-time model and was examined in a Mercedes C-Class vehicle. In this article, the
simulation results and the real-time measurements are presented. The results show that the proposed controller has high
effi ciency in disturbance rejection and lower sensitivity towards parameter changes compared to a model predictive control
(MPC) structure. |
Key Words:
Path-tracking control · Robust control · Convex optimization · Autonomous vehicles · Nonlinear control
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