Synergistic control of hilly tractor slip: A dual-parameter approach utilizing BP neural network

To address the coupling issue of longitudinal and lateral slip in tractors operating on lateral ramps in hilly and mountainous terrain, this study proposes a slip cooperative control method that enhances lateral stability. An optimal longitudinal slip index, constrained by lateral slip, is established as the primary control objective. A BP neural network-based model for predicting longitudinal and lateral slip is developed using training data collected from a self-built experimental platform under various conditions, including different lateral ramp angles, soil moisture levels, and traction forces. The study introduces a dual-parameter cooperative control architecture that combines “throttle opening-traction” control modes. This includes two operational modes: traction control and “throttle opening-traction” control. The controller parameters are optimized using an improved ITAE (Integral of Time Absolute Error) performance index, integrated with a particle swarm optimization algorithm (PSO-APID). Simulations conducted in Matlab/Simulink verify the effectiveness of this method under typical hilly terrain conditions. The results show that the proposed traction control mode, “throttle opening-traction” control mode, and their combined control mode effectively stabilize the longitudinal slip within the optimal range. Under the combined control mode, the mean lateral slip is reduced by 12.4% compared to the uncontrolled case. Additionally, under compound excitation, the PSO-APID controller demonstrates a shorter response time and smoother throttle and traction curves than conventional PSO-PID and classical PID algorithms, exhibiting superior dynamic characteristics. While maintaining the slip within the efficient range of 19%, the lateral slip is constrained to within 6%, providing theoretical support and a technical pathway for the intelligent control of agricultural equipment in complex terrains.