Research And Application Of Paper Quality Index Control In Papermaking Process Based On Predictive Control

Paper packaging has the obvious advantages of low price,light texture,easy processing and molding,good printing performance and so on.It is the most widely used packaging in the market at present.It is used in the consumer industry of end products,such as food,tobacco and alcohol,express delivery,electronics and appliances,daily chemical products and so on.The main raw material of packaging paper is waste pulp.According to the statistics of China Paper Association,the total production of waste pulp in 2020 was 53.63 million tons,an increase of 0.22% over 2019,and the total consumption was 56.32 million tons,including 53.83 million tons of domestic waste pulp.Therefore,the improvement of the quality of paper products,the development of functions and the improvement of the efficiency of paper products are particularly important.As the most important part of modern paper industry,the main function of automatic control of paper machine is to solve and improve the production of finished paper that meets the quantity,quality,function and profit from the perspective of control.The traditional algorithm can not meet the control of modern complex paper machine,so we need to find a new control algorithm to control the paper machine.The main research content of this thesis is to study the control of papermaking process,how to control the quantitative and moisture of paper efficiently,quickly and accurately,and improve the efficiency and benefit of papermaking process.The main research contents are as follows:(1)The paper making process is modeled.The papermaking process is a multivariable control system process.Therefore,analyze the multivariable system and various modeling methods,then study the papermaking process and analyze the mechanism of each part,seek the relationship characteristics of the main quantitative and moisture influencing factors in the papermaking process,and establish a mathematical model of the papermaking process which is close to the real process.The established mathematical model should consider some characteristics of the papermaking process,including uncertainty,incompleteness,nonlinearity,time delay and strong coupling,and ignore the disturbance of external environmental factors.Then the signal of each parameter is detected,and an advanced control algorithm is proposed according to the process of papermaking process.(2)A new control algorithm is proposed.When controlling the paper machine,the control equipment with PID regulator is adopted.The usual method is to adjust each part separately to stabilize each influencing factor,which makes the paper manufacturing process too cumbersome.It needs to repeatedly adjust the parameters of the controller for many times to achieve the optimal processing effect.Because the effect of paper processing is too complex and the adjustment time is long,it can not achieve good control effect.Now the complex paper machine can not be well controlled.For the regulation of quantitative moisture and ash in the papermaking process,they are disturbed by many factors and are not easy to measure.Therefore,if the papermaking process is only controlled by PID,the quality of the paper will not be guaranteed.The dynamic control matrix has the characteristics of robustness,and the requirements for the model parameters of papermaking process are not high.Therefore,firstly,this thesis will design the PI + DMC controller combined with the advantages of PID controller.Secondly,there are no constraints in the process of predictive control at ordinary times,but there are many constraints in the process of papermaking,such as full on-off position control of dilution water valve,rotation speed of valve,etc.in order to solve this series of problems,this thesis will use particle swarm optimization(PSO)to solve this problem,and add particle swarm optimization algorithm in the process of dynamic matrix measurement and control,The PI + DMC controller based on particle swarm optimization is designed.Finally,in order to get better control,this paper improves the particle swarm optimization algorithm to obtain the PI + DMC controller based on the improved particle swarm optimization algorithm,and then carries out simulation test through MATLAB.The algorithm can achieve the expected effect.