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Preview-Based Path-tracking Stability Control with Vehicle Dynamic Uncertainty via Robust Weighted LPV/H∞ Technique.
Wenliang Cao1, Enlin Zhou1, Zhicheng He1
1State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle, Hunan University, 410082 Changsha, China.
ISA Transactions
|June 26, 2024
Summary
This study introduces a robust path-tracking control for autonomous vehicles, enhancing stability and performance against disturbances. The novel technique ensures reliable autonomous driving even with uncertainties.
Area of Science:
- Robotics and Control Systems
- Automotive Engineering
Background:
- Autonomous vehicles require precise path-tracking for safety and performance.
- External disturbances and model uncertainties challenge existing control systems.
Purpose of the Study:
- To develop a preview-based robust path-tracking control technique for autonomous vehicles.
- To enhance lateral stability and tracking performance under disturbances and uncertainties.
Main Methods:
- Developed a vehicle-road dynamic model with norm-bounded tire uncertainty and time-varying parameters.
- Formulated an optimal preview model using fuzzy logic and estimated sideslip angle via a sliding mode observer.
- Constructed a linear parameter-varying (LPV)/H∞ controller for robustness and stability.
Main Results:
- The proposed controller significantly improves path-tracking performance.
- Excellent lateral stability was maintained across the entire parameter space.
- The technique effectively handles external disturbances and modeling uncertainties.
Conclusions:
- The preview-based robust path-tracking control technique ensures reliable autonomous vehicle operation.
- This method offers enhanced safety and performance for self-driving systems.
Keywords:
H∞ techniqueLinear parameter varying (LPV) controlPreview-based path-trackingSliding mode observerMore Related Videos
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