Optimal H_∞ Control for Lateral Dynamics of Autonomous Vehicles

Area of Science:

• Robotics and Control Systems
• Autonomous Vehicle Navigation
• Computer Vision

Background:

• Autonomous vehicles require precise lateral control for safe navigation.
• Real-time trajectory following necessitates robust control strategies.
• Variations in vehicle speed can challenge lateral stability and tracking accuracy.

Purpose of the Study:

• To design and validate a model-based H∞ vehicle lateral controller.
• To minimize position and orientation tracking errors for autonomous vehicles.
• To ensure robust performance against longitudinal speed variations.

Main Methods:

• Development of a model-based H∞ lateral controller.
• Integration of video-processing and lane-detection algorithms for real-time trajectory computation.
• Utilizing Linear Matrix Inequality (LMI) optimization for controller design.
• Co-simulation in Matlab/Simulink and Carsim for validation.

Main Results:

• The controller effectively minimizes position and orientation tracking errors.
• Achieved robust closed-loop system performance despite longitudinal speed changes.
• Demonstrated good control performance in a simulated environment.

Conclusions:

• The proposed H∞ lateral controller is effective for autonomous vehicle trajectory following.
• The model-based approach provides robustness against speed variations.
• Co-simulation validates the practical applicability of the control strategy.