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Grain drying process control is a predictive control model of a high accuracy intelligent,in order to improve the reliability and adaptability of the grain drying process control,proposed a predictive control model for grain drying process intelligent weighted composite prediction based on the first constraint parameter model and control function of grain drying process control is established,using PID control method fuzzy decision control model design,prediction method of adaptive neural network using weighted combination,improve the control process of fitness and support.Then we use TMS320VC5509A as the core control chip,the control system design,software development and control of grain drying prediction in the embedded kernel of Linux2.6.32 platform,design and Realization of control system optimization prediction.Finally,the application of the test and analysis,the results show that the system is used to control the grain drying process,and effectively adjust the temperature and humidity of grain drying,the control accuracy is better,and the human-computer interaction is better.