Study On Predictive Control Of Water Content In Continuous Cross-flow Grain Drying Tower

Drying of food is an extremely complex process,and food drying technology involves many interdisciplinary disciplines,including agricultural product processing,food,food,and chemical.The grain drying process is a process that consumes a lot of energy.The drying process seriously affects the quality of food and processing costs.Dry food is an important part of agricultural production.Farmers have worked hard in the long process of planting and harvesting crops.In order not to waste the labor results of farmers,increase the grain yield and ensure a bumper harvest.The effect is to increase the research intensity of grain drying and analyze each link of grain drying in a deeper way.Grain drying not only exists in physical processes,but also has complex chemical changes.In this era of material richness,people's requirements for food are constantly improved.In the drying process,not only food safety but also food safety must be guaranteed and the nutrition and color of the food.In the early years,the design of grain dryers was too backward.Therefore,in the process of grain drying and processing,it relied on empirical methods to judge the effect of grain drying.In recent years,a large number of researchers have used digital computers to simulate the drying process of grain,so that the understanding of the grain mechanism is more thorough.Through this refined research,the automation level of the drying process is greatly improved.The grain drying process is an essential part of grain storage,but the process is a complex process with large hysteresis,non-linearity and multi-disturbance.In order to process food that meets safe storage,it is necessary to carry out the grain drying process.In-depth theoretical research.In this paper,based on the drying characteristics of corn,a detailed theoretical study on the grain drying process was carried out.The working process of the continuous cross-flow grain drying tower studied in this paper was introduced.The model of grain drying process was established and the effect of corn was affected.The maim factors of the moisture content of the machine,including the moisture content of the corn,the speed of the grain-discharging motor and the temperature of the high-temperature air,were simulated and analyzed.A model predictive control system was built for the continuous cross-flow grain drying tower,and the least squares support vector regression machine was used as the system prediction model.The genetic algorithm was used to optimize the parameters of the least squares support vector regression machime to obtain the optimal.The amount of control is used to achieve predictive control of the moisture content of grain.Through simulation comparison and analysis,this method can effectively predict and control the grain moisture content of grain,reflecting the stability and superiority of model prediction.