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Linear Quadratic Regulator Control of Vehicle Active Front Steering Considering Aerodynamic Characteristics
Junzhi Hu1, Conghao Liu1, Yunlong Wang2
1School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China.
Sensors (Basel, Switzerland)
|July 15, 2026
Summary
This study improved vehicle handling stability and driving safety using a vehicle dynamics model and an active front steering controller. The linear quadratic regulator (LQR) algorithm enhanced steering performance and ensured a stable body attitude, even in crosswinds.
Area of Science:
- Vehicle Dynamics and Control
- Automotive Engineering
- Aerodynamics
Background:
- Ensuring vehicle handling stability and driving safety is crucial, especially for special vehicles operating in challenging conditions.
- Accurate aerodynamic modeling is essential for realistic vehicle dynamics simulations.
Purpose of the Study:
- To enhance the handling stability and driving safety of a special vehicle.
- To develop and validate an active front steering (AFS) controller using the linear quadratic regulator (LQR) algorithm.
Main Methods:
- Developed a vehicle dynamics model in TruckSim and a two-degree-of-freedom model in Simulink.
- Obtained and integrated vehicle-specific aerodynamic coefficients into the TruckSim model.
- Designed and implemented an LQR-based AFS controller using MATLAB/Simulink.
Main Results:
- The integrated aerodynamic model improved simulation accuracy.
- The LQR-based AFS controller effectively regulated the vehicle's yaw rate and sideslip angle.
- Simulations demonstrated improved steering performance and stable body attitude under crosswinds.
Conclusions:
- The LQR algorithm significantly enhances handling stability and driving safety for the special vehicle.
- The developed AFS control strategy provides precise tracking of desired vehicle motion.
- Accurate aerodynamic modeling and advanced control algorithms are key to improving vehicle performance.
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