RESEARCH ON ADVANCED COMPENSATION CONTROL STRATEGY FOR SOYBEAN COMBINE HARVESTER HEADER HEIGHT BASED ON AREA ARRAY LiDAR

For the automatic control of soybean harvester header height, this study uses Area array LiDAR for header height detection. An improved quartile range algorithm is used to dynamically remove outliers under crop residue interference. Linear, quadratic, and cubic nonlinear terrain fitting models are established based on the surface undulation characteristics of soybean fields. The Huber loss function is introduced to enhance the robustness of parameter estimation. The balance between model complexity and fitting goodness is quantified using Bayesian information criterion (BIC), and the model intercept term with the smallest BIC value is selected as the terrain reference height. Aiming at the hysteresis characteristics of valve controlled asymmetric hydraulic cylinders, a telescopic dual-mode transfer function model is established, and a Bang Bang switch lead compensation strategy with position threshold is proposed. By predicting the trend of terrain changes, the electromagnetic directional valve is triggered in advance when the height error of the header exceeds the set threshold, effectively reducing the system response delay. Field comparative experiments have shown that at a working speed of 1m/s, the automatic control mode significantly improves the uniformity of cutting compared to the manual mode. When the cutting threshold is set to 20, 25, and 30mm, the coefficient of variation of cutting height is reduced by 2.13%, 1.71%, and 0.55%, respectively. Moreover, the automatic mode maintains a gentle distribution characteristic within the threshold range of 15-35mm, verifying the strong robustness and control accuracy advantages of the designed system in complex farmland environments.