An entropy-driven dual-mode adaptive operation control system for heavy-haul trains
By using an entropy-driven dual-mode adaptive operation control system, the problems of decreased control accuracy and stability of heavy-haul trains have been solved. This system enables the recovery of automatic driving reliability and control performance under complex operating conditions, and adapts to changes in air resistance and gradient.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING JIAOTONG UNIV
- Filing Date
- 2026-06-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing heavy-haul train operation control methods are unable to reflect the interaction between carriages and the compression constraints of the coupler and buffer device, resulting in decreased control accuracy and error accumulation. Furthermore, adaptive control methods introduce unnecessary parameter fluctuations when operating conditions change, affecting the stability of the control system and the reliability of automatic driving.
An entropy-driven dual-mode adaptive operation control system is adopted. Through HHT dynamic state acquisition, desired trajectory reading, velocity error generation, positioning error generation, adaptive parameter estimation, sliding window sparse sampling, data quantization and entropy calculation, mode switching logic and HHT execution unit, it realizes real-time response and stable control to changes in air resistance and slope.
It improves the reliability of automatic driving of heavy-haul trains under complex working conditions, reduces unnecessary parameter updates, ensures the stability of control performance in the stable phase and rapid recovery when working conditions change abruptly, and maintains the traction-braking regulation effect.
Smart Images
Figure CN122402618A_ABST