Research On The Intelligent Control Model Of The Pellet Mill

Production process control and automation on industrial control computer has been widely used in chemical and medical industry, on the other hand, it received rare attention by feed plant. Currently, it has been greatly improved in feed plant with the development of computer-aid production process control and automation system during the ninth and tenth five-year technique promotion plans. However, computer aided production control system is mainly focused on the production automation, yet leaves the problem how to improve product quality intact. From actualities of most feed plant, lots derived information are not dealt with through analyzing just recording, which brings value loss and waste of feed plant because problems and troubles cannot be handled in time. On the other hand , there are many factors with uncertainty influencing the quality of feed pellet, and traditional approachs do not facitating modeling the nonlinear relationships with uncertainty, therefore. Radial Basic Function (RBF) neural network is adopted to establish the mathematic model for feed drilling intelligent control system for its characteristic of approximating the relationships between input variables to output variables to real-word relationships in any precisions.Based on the study of product feed pellet production process, a Radial Basic Function (RBF) neural network is proposed to build the drilling model, which has three lays. Based on experiment design and factor analysis, conditioning temperature, conditioning coisture, feeding speed and protein content are adopted as input of network while hardness is employed as the quality of feed pellet, as well as the output of neural network.Modeling and realizing of RBF network requires outstanding programming capability, which greatly prevent the neural network technique from spreading and application. However, Matlab software provides an effective toolkit called Neural Network Toolbox (NNT) to solve this problem. In this paper, mathematic model for feed drilling intelligent control system is established based on the introduction of RBF neural network's principal and algorithm, along with RBF neural network model building, training, simulating and programming.