智能预测控制在谷物干燥过程中的应用研究

Application of Intelligent Predictive Control in Grain Drying Process

摘要:

谷物干燥过程控制是一个高精度智能预测控制模型,为了提高谷物干燥过程控制的可靠性和自适应性,提出一种基于加权组合预测的谷物干燥过程智能预测控制模型,首先建立谷物干燥过程控制的约束参量模型和控制目标函数,采用模糊决策的PID控制方法进行控制模型设计,采用加权组合预测方法进行自适应神经网络加权,提高控制过程的适应度和支持度；然后选用TMS320VC5509A作为核心控制芯片,进行控制系统设计,在Linux2.6.32嵌入式内核平台中进行谷物干燥预测控制软件开发,实现预测控制系统优化设计；最后进行应用测试分析,结果表明,采用该系统进行谷物干燥过程的控制,能有效调节谷物干燥中的温度和湿度,控制精度较好,人机交互性较好。

Abstract:

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.