# Grain Sieve Loss Fuzzy Control System in Rice Combine Harvesters
## 1 Introduction  
The use of combine harvesters for harvesting rice fields is rapidly increasing year by year in China as the planting area and yield keep increasing [1]. As there are different rice varieties and harvesting times, the harvesting performance of the combine harvesters significantly fluctuates under different crop-harvesting conditions. The automation of the combine harvesters is one good way to guarantee the harvesting performance, and the flagship combine harvesters made by European companies have realized the functions of operation process fault diagnosis, forward speed control, adaptive threshing and cleaning, chassis lift control, and so on, significantly improving the overall operating efficiency and performance [2; 3; 4; 5; 6; 7]. However, the relevant research on the state monitoring of the operation of combine harvesters is still in its infancy period in China. Most combine harvesters merely have engine revolution speed monitoring devices installed, parameter settings can only be adjusted when combine harvesters stop working based on the experience of the operator, and the cleaning performance varies dramatically. The cleaning device as one of the core parts of the machine and cleaning performance is another one of the major factors to weigh the performance of the whole machine. However, to date, automatic control systems for the cleaning units are not commercially available.  
Scientists have carried out enormous relevant research on the cleaning processes of combine harvesters, and some investigations can be found investigating the effect of fan revolution speed, the area of the fan air inlet, sieve opening, and sieve vibration amplitude on the movement of grains and material other than grain (MOG) in the cleaning shoe, and several corresponding mathematicalmodels have been developed [8; 9; 10; 11]. Better insight into the characteristics of the cleaning process was obtained owing to the interpretation of these mathematical models. However, a complete mathematical model that is applicable to the cleaning process would need to include several equations that are difficult to obtain and would probably be very complex. On the other hand, on the basis of analyzing the existing experiment data, and comparing the merits and drawbacks of the existing control strategy, a common drawback of most standard modeling and control techniques is that they are always based on an accurate mathematical model, and cannot make effective use of the expert knowledge of experienced engineers and operators [12]. The fuzzy control methodology, which combines the advantages of the white-box and black-box approaches, is widely used in agriculture machinery control systems, and improves the performance greatly [13; 14; 15]. Therefore, utilizing sensor technology and fuzzy control theory to develop a control system that can monitor grain sieve loss and the main working parts of the cleaning system that can be controlled by the established control strategy in real time is an efficient way to improve their cleaning adaptability. On the basis of studying the grain sieve loss sensor [16; 17], this paper mainly studies the correlation between grain sieve loss and the related working parameters (fan speed, guide plate angle, and sieve opening) to determine the main factors affecting cleaning performance; then, a cleaning process fuzzy control system was designed to maintain the cleaning system with a good cleaning performance.