Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference (한국펄프종이공학회:학술대회논문집)
- 2004.11a
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- Pages.221-232
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- 2004
Modeling and Identification of Paper Plants based on PRS
PRS를 이용한 제지공정의 인식 및 모델링에 관한 연구
Abstract
Paper process is complex and multivariable system. Identification of a paper process model is imperative for the development of predictive control method. 13-level Pseudo-Random Sequence Signals were used to identify the plant model in which the neural network model was considered model as a real paper process. Results of simulations for identification using 13-level PRS signals and Prediction Error Method are compared with plant operation data. From the comparison, we can see that the dynamics of the model show good agreement with those of real plant.