Design on fuzzy control system of grain particles transport based on network prediction

It is difficult to establishe accurate mathematical model to realize the closed-loop control,because of the complex nonlinear relationship among the wind speed,pressure loss,feed-gas ratio and other parameters in grain partieles pneumatic transport.To solve this problem,with CXLD50 suction pressure mixed conveying mobile grain sucking machine as the research platform,fuzzy control strategy was put forward with the material flow prediction of BP neural network as feedback loop.The system uses the material flow prediction model based on neural network tools which could quickly and conveniently online measured two-phase flow.After comparing the model output flow of prediction and expectation,it was input to the fuzzy controller for judgement and output.Simulation showed that the system has rapid response,achieving ideal output in 50 s and strong anti-interference ability,keeping deviation stable in ±0.5 kg/s so that the fuzzy control system could improve the signal of off-line measurement feedback lag and raise the stability of transport system.