Robust slip-ratio regulation for agricultural tractors with transformer-enhanced speed estimation
Year: 2026
Type: article
Abstract: In heavy-draft field operations such as plowing, spatially varying soil properties and traction-load fluctuations can cause excessive tractor wheel slip, complicating longitudinal-speed estimation and slip-ratio regulation. To address this issue, this study proposes a robust slip-ratio regulation method integrating Transformer-enhanced extended Kalman filtering (EKF) with boundary-layer adaptive super-twisting sliding mode control (ASTSMC). First, a Transformer network adaptively scales the EKF process-noise covariance using causal temporal features, thereby adjusting the fusion between the model prediction and the non-ideal onboard speed observation to improve longitudinal-speed estimation. Second, the estimated speed is used to calculate the slip-ratio feedback for a boundary-layer ASTSMC, which combines adaptive gains with a continuous saturation function to improve robustness and reduce torque chattering. Finally, the Transformer-EKF was evaluated using full-scale tractor field data, and the slip-ratio controller was validated through hardware-in-the-loop testing on an NI-PXI real-time platform. Evaluation results showed that, during multi-gear-shift transport, the Transformer-EKF reduced MAE and RMSE from 0.1814 and 0.2403 km/h to 0.1286 and 0.1668 km/h, respectively; during steady operation, they decreased from 0.2764 and 0.3153 km/h to 0.1579 and 0.2167 km/h. HIL tests showed that ASTSMC reduced front- and rear-wheel slip-ratio settling times to 0.386 and 0.830 s, respectively, versus 0.834 and 1.672 s for PID, 0.756 and 1.098 s for conventional SMC. ASTSMC also reduced the corresponding steady-state standard deviations by 32.8% and 30.2% relative to PID. Taken together, the field-data estimation results and HIL control results demonstrate the potential of the proposed framework for adaptive tractor slip-ratio control in unstructured farmland environments.
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,870
Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Hainan Association for Science and Technology, Major Projects of Guangdong Education Department for Foundation Research and Applied Research, Henan Provincial Science and Technology Research Project, Science and Technology Innovation Talents in Universities of Henan Province, Basic and Applied Basic Research Foundation of Guangdong Province
OpenAlex ID: W7213970956