The combing process of gill machine is an important link in the wool spinning technology.Inorder to improve the quality of products,it is necessary to study the new autoleveling device whichuses the modern control the...The combing process of gill machine is an important link in the wool spinning technology.Inorder to improve the quality of products,it is necessary to study the new autoleveling device whichuses the modern control theory and microcomputer science.We have to set up a mathematicalmodel for object:As the woolen yarns (both input and output) are complex random process,it issuitable for CARMA (controlled autoregressive-moving average) to describe the object by meansof time series analyses of models.展开更多
In textile industry, carding process has decisive influence on produced yarn quality. From the system theoretic point of view, it is marked by stochastic disturbance, long delays, and parameter variation. So, a cardin...In textile industry, carding process has decisive influence on produced yarn quality. From the system theoretic point of view, it is marked by stochastic disturbance, long delays, and parameter variation. So, a carding process is difficult to control with traditional control algorithms (such as PID). In this paper, a weighted adaptive generalized predictive control (GPC) law was developed to control such a process. The experimental results show that GPC autoleveller controller could greatly reduce the sliver’s standard deviation and reject disturbance.展开更多
文摘The combing process of gill machine is an important link in the wool spinning technology.Inorder to improve the quality of products,it is necessary to study the new autoleveling device whichuses the modern control theory and microcomputer science.We have to set up a mathematicalmodel for object:As the woolen yarns (both input and output) are complex random process,it issuitable for CARMA (controlled autoregressive-moving average) to describe the object by meansof time series analyses of models.
基金National Innovation Foundation ResearchProgram of Small-Medium Sized Enterprise(No.03C26113200125)
文摘In textile industry, carding process has decisive influence on produced yarn quality. From the system theoretic point of view, it is marked by stochastic disturbance, long delays, and parameter variation. So, a carding process is difficult to control with traditional control algorithms (such as PID). In this paper, a weighted adaptive generalized predictive control (GPC) law was developed to control such a process. The experimental results show that GPC autoleveller controller could greatly reduce the sliver’s standard deviation and reject disturbance.
