Research On Intelligent Control System Of Purification Workshop

In recent years,the purification workshop has been attached great importance by the governments of all countries and well-known international enterprises,and has been widely used in industries that are particularly sensitive to environmental pollution,such as semiconductor production,biochemical technology,precision machinery,pharmaceutical and other industries.This thesis studies the control of injection purification workshop in a pharmaceutical enterprise in Heilongjiang Province.Due to the coupling and complexity of wind speed,temperature and humidity in the production process,the traditional PID control can not achieve satisfactory control effect.In view of the above problems,this paper uses predictive control theory,fuzzy control theory,fractional order control theory to control the purification workshop system,so as to make the air cleanliness,temperature and humidity in the purification workshop reach the corresponding national standards and improve the purification efficiency.The main research contents of this thesis include:Firstly,the control system of the purification workshop is modeled.According to Navier Stokes equation of hydrodynamics and Galerkin method,the wind speed control model of purification workshop is obtained.Then,the mathematical models of heater temperature,humidifier temperature,fan temperature,heater humidity,humidifier humidity and fan humidity are obtained by using the method of system identification,which lays the foundation for the design of controller.In order to make the wind speed in the workshop uniform and improve the purification efficiency,a fuzzy fractional order controller based on grey prediction is designed.The gray prediction method is used to process the wind speed sampling data,and the prediction error and error change rate are used as the input of the fuzzy fractional order controller.After the fuzzy reasoning,the parameters of the fractional order controller are updated continuously to realize the real-time optimization of the controller parameters,and the simulation results are compared with the traditional PID controller in MATLAB.In order to reduce the coupling of wind speed,temperature and humidity,a generalized predictive decoupling control method based on adjusting the error weighting factor of reference input variation is studied.When the temperature,humidity and wind speed change in the system,the optimal control law is calculated to minimize the cost function of the system,so as to reduce the interaction between the system variables.In order to further improve the decoupling effect,when the set value of the input variable changes,the corresponding error weighting factor is calculated,and it is input into the GPC to eliminate the impact of the change of the set value of the multi variable.The effectiveness of the algorithm is verified in MATLAB.Finally,the hardware and software design of the intelligent control system of the purification workshop is completed.Including the overall design of the hardware system,hardware selection,related circuit design,and complete the system software design in the ccs6.0 software platform.