Research Of Fuzzy Neural Network Controller On The Forage Dryer Control System

With the development of the global economy, the standard of people’ living was continuouslyimproved, improving the quality requirement of the aquaculture products and animal husbandryproducts, increasing the demands of the forage products. Our contry was a power animalhusbandry contry, and the forage grass resources were abundant, but it was lack of dryingequipment, and the grass products was processed in the traditional natural drying method, theforage grass forage value’s loss was severe, and the processing time was long, the quality was poor,the waste was serious, and it was difficult to form the commercialization and expand domestic andforeign markets in the restriction of the weather conditions.The forage dryer was essential for the forage production as the key equipment to produce highquality forage meal and develop the plant protein feed resources. People often caused theeconomic losses because of the improper controlling of the product parameters such astemperature、humidity and so on. Therefore, it could reduce the economical losses, and improvethe quality of the forage, and enhance the competitiveness of the forage product, if you have had agood control technology of the drying.This paper presented the composition structure and the control requirements of the foragedryer control system and discussed the main factors that affected forage dryer control system andthe measures to eliminate adverse factors. It analysed the principle of fuzzy control、BP neuralnetwork control. It simulated the fuzzy control、neural network control and the BP neural networkcontrol using MATLAB/Simulink, and it determined the control system used the fuzzy neuralnetwork controller, and its effect was better than the other controllers.It designed and debuged the software program of fuzzy neural network digital controller onthe basis of perfecting forage dryer control system. The test results showed that the control effectof fuzzy neural network controller could meet the requirements of control system performance,and it had a very good robustness and adaptability, and it achieved a good control effect.