Robust dynamic nonlinear control using adaptive gain estimation for ground vehicles under parametric uncertainties...

Area of Science:

• Automotive Engineering
• Control Systems
• Robotics

Background:

• Vehicle dynamics control is crucial for safety and performance.
• Existing methods struggle with uncertainties and external disturbances.
• Active Front Steering (AFS) and Rear Torque Vectoring (RTV) offer advanced control capabilities.

Purpose of the Study:

• To develop a robust dynamic nonlinear control strategy for vehicles with AFS and RTV.
• To enhance trajectory tracking accuracy under uncertain conditions.
• To improve disturbance rejection and lateral velocity estimation.

Main Methods:

• Implementation of high-order sliding mode (HOSM) estimators with adaptive gains for control.
• Design of a novel HOSM observer with adaptive gains for lateral velocity reconstruction.
• Validation through numerical simulations using CarSim software.

Main Results:

• The proposed controller demonstrated accurate trajectory tracking despite parametric uncertainties.
• Superior transient behavior and disturbance rejection were observed during a double-lane-change maneuver.
• The adaptive HOSM observer effectively reconstructed lateral velocity under dynamic conditions.

Conclusions:

• The adaptive HOSM control strategy offers a robust solution for trajectory tracking in vehicles with AFS and RTV.
• The integrated observer enhances performance in dynamic driving scenarios.
• The approach significantly outperforms conventional methods in challenging maneuvers.