Integrated Control Method Of Food Drying Based On Information Fusion And Its Application

Our country has a large population base,which is a big country of grain production and a big country of grain demand.There are many small farmers in the grain drying process to establish control technology and model realization and application become the research hotpots,the urgent need of grain drying process to achieve the purpose of automation and mechanization.In order to improve the productivity of agricultural products,we should reduce the waste of food and labor consumption in order to guarantee the uniformity of the grain moisture.However,in the process of grain drying,there are many problems,such as time-varying,nonlinear and large lag,so that the complexity of the grain drying process is increased,and the difficulty of automatic production is increased.In the past,there are many drawbacks.To establish a predictive control model not only high complexity and huge amount of data by using artificial neural network algorithm;differential equation,heat and mass transfer equation and other ways to build does not need many data but still did not reduce the complexity.Therefore,in recent years,the focus of research has shifted to the use of fuzzy control,neural networks and online detection methods and strategies to achieve real-time control.Fuzzy control and neural network control belong to the category of expert system.But it is characterized by the use of artificial experience to form an expert system database,need to take up a lot of storage space.Therefore,the key point of this paper is to select the appropriate forecasting method and the more appropriate grain drying process control strategy.This paper designs a temperature predictive controller based on information fusion based on information fusion and uses the fuzzy immune PID algorithm to control the drying process based on cross-flow drying principle,and builds a data fusion model based on information fusion The fuzzy immune PID control model of temperature predictive controller is simulated and verified.The main contents of this paper are as follows:(1)The establishment of temperature prediction model based on information fusion,the feedback correction of the model.The temperature predictive controller based on information fusion is designed,and the predictive control is suitable for food process control with time-varying,nonlinear and largetime-delay.(2)Fuzzy immune PID algorithm controller,the overall design,fuzzy control can be a wealth of experience in the control process used to further improve the control accuracy.(3)The simulation of the entire controller validation,analysis of problems.