Research And Implementation Of Wind Pressure Intelligent Control For Cigarette Factory Process Of Wind-Power And Dust Removal System

Stable production for Cigarette Factory Process of Wind-Power and Dust RemovalSystem needs a stable supply of demanding of wind. Studying advanced controltechnology and improving the level of the intelligent system is always thedevelopment direction for Process of Wind-Power and Dust Removal System.This paper first discusses Wind-Power and Dust Removal System, analyses thestructure of the system, network communication and data sharing and the controlprinciple. Pipe line characteristic curve is studied. At the same time, Fan stable statepoints and influence factors of fan energy consumption is analyzed. Through thecollection of the data analysis, the conclusion is proving that the greate air volumewill make the high energy consumption of the fan. Implementation of the systemexecutive device for the influence of various parameters of mathematical model isanalyzed. the system input and output model is presented. Wind pressure and airmathematical relationship model is studied, the wind pressure, air system predictionmathematical model is established.In this paper the defects of the conventional PID control system is analyzed. Thewind control BP neural network PID control is introduced. BP algorithm and thedefects of the standard BP algorithm is studied. The structure of BP algorithmself-adaptive learning rate is constructed. Through analyzing Matlab simulationresults, the superiority of self-adaptive learning rate BP algorithm is proving. The PIDcontroller ‘s BP neural network structure is structured, realizing the conventional PIDcontroller and self-adaptive learning rate for BP neural network algorithm thecombination. The concrete implementation scheme of the BP algorithm PID controlleris put forward for this system. The PC and PLC under a common division completethe BP neural network of PID control of wind. Finally the system model parameters identification program and the self-adaptivelearning rate BP neural network algorithm program is given in InTouch scriptenvironment. The BP neural network PID controller this paper studied is applied toCigarette Factory Process of Wind-Power and Dust Removal System. Relative to theconventional PID controller, it has obvious superiority. The PID parameters’auto-tuning and adaptive function is satisfied. The intelligent control of the windsystem is realized.