基于状态扩张观测器的个性化转向回正目标曲线构建方法
By combining state extension observer and adaptive sliding mode control, the self-evolution of personalized steering return target curve is realized, which solves the problem of insufficient driver preference adaptability in traditional methods and improves the robustness and accuracy of steering control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JILIN UNIVERSITY
- Filing Date
- 2026-05-18
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional methods for constructing steering return target curves cannot adapt to the individual preferences of different drivers, nor can they meet the real expectations of drivers under complex working conditions, resulting in rigid return characteristics and insufficient robustness and tracking accuracy.
The system employs an extended state observer (ESO) combined with recursive least squares (RLS) to learn driver operating preferences online. It uses an adaptive sliding mode (ASM) control law to achieve the self-evolution of personalized homing target curves, compensate for system uncertainties and model errors in real time, and generate continuous and smooth personalized homing trajectories.
It achieves dynamic adjustment of the return-to-center characteristics based on the driver's personalized preferences, improving robustness and steering quality under complex working conditions, and ensuring smoothness and high-precision tracking of the return-to-center process.
Smart Images
Figure CN122186255B_ABST