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Study of Advanced Control on Polymerization Temperature of Chlorinated Polyethylene
Author: JiangHaiBo
Tutor: ZhouYiLin
School: Qingdao University of Science and Technology
Course: Detection Technology and Automation
Keywords: Chlorinated Polyethylene Internal Model PID control Neural Networks Kingview Dynamic Data Exchange
CLC: TP273
Type: Master's thesis
Year: 2008
Downloads: 161
Quote: 0
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Abstract
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In recent years, with the vigorous development of the petrochemical industry , a variety of petrochemical products in many areas has been widely used. Wherein , chlorinated polyethylene (CPE) , as one of the impact modifiers in polyvinyl chloride (PVC) , because of simple raw material , low production cost , and have an important role in the plastic and rubber , so the demand for international and domestic the amount was a rising trend . The CPE's production process is carried out in a batch reactor chloride polymerization reactor temperature is an important parameter to affect the reaction , is directly related to the quality of the product . The polymerization reaction is highly exothermic , the temperature has a big lag , when degeneration and non-linear characteristics of conventional PID control can not meet the control requirements , and to this end we propose the use of advanced control algorithms to give an effective transformation of try . CPE production process of the papers to a chemical plant in Qingdao , in-depth analysis of the characteristics of the the CPE Chlorinated polymerization reaction temperature control difficult , advanced internal model PID control method based on neural network is proposed . Through self- learning neural network to adjust degeneration has a strong adaptive ability of the nonlinear and time , internal model control with simple parameter adjustment , track performance and good features , IMC-PID control method is designed in the framework of the internal model control PID controller system lag better control effect and disturbance . Neural network internal model PID can give full play to the advantages of both , CPE polymerization temperature accuracy and smooth control . The experimental results show that the neural network model PID control with good self- adaptability, robustness and anti-interference ability , can effectively improve the stability of the control system . To be able to image , intuitive display and control CPE polymerization production process , the paper design based monitoring software configuration king . Kingview excellent real-time monitoring and dynamic display function , Matlab has a powerful mathematical calculation ability , can achieve the complexity of advanced control algorithms , able to achieve the configuration king and Matlab data communications through the use of dynamic data exchange technology ( DDE ) to provide for the application of advanced control method in industrial practice can be an effective way to learn .
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