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Abstract. Combine harvesters are not only used for threshing crops but also for separating, cleaning, and storing grains. Additionally, they have different forward speeds when crop conditions vary. It is important to adjust and optimize the control strategy for these machines to adapt to varying conditions, such as crop variety, cropping intensity, and cutting width. Previous studies have provided considerable knowledge about the working principles of the operation control systems of combine harvesters based on operator‘s experiences and data-based models. However, important information mined from sensor sample databases is rarely used to control the forward speed of a combine harvester, and thus, it remains unknown even by skilled drivers and experts. In this article, a multi-parameter fuzzy control strategy (FCS) for the forward speed of a combine harvester based on knowledge discovery in databases (KDD) is proposed. The main goal of the multi-parameter FCS for forward speed is defined as finding the optimal trade-off among the acceptable weight factors for the cutting table auger, conveyer trough, and threshing rotor to achieve the desired low loss rate and high feeding quantity. Simulation analyses and experimental evaluations revealed that the harvesting performance of a combine harvester using multi-parameter FCS is better than that using ordinary FCS regarding average feeding quantity and average unit loss rate; additionally, the stability and response of the controller using multi-parameter FCS are superior to those using ordinary FCS.
Chen et al. (Mon,) studied this question.