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| Paper Basis Weight and Moisture Decoupled Control Based on RBF Neural Network |
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| DOI： |
| Key Words:RBF neural network; basis weight; moisture; decoupling control |
| Fund Project:江苏省制浆造纸科学与技术重点实验室开放基金项目（201010）。 |
| Author Name | Affiliation | | 尤 斌1 | 1.南京林业大学江苏省制浆造纸科学与技术重点实验室，江苏南京，210037 | | 彭 晗2,* | 2.南京林业大学化学工程学院，江苏南京，210037 | | 胡慕伊1 | 1.南京林业大学江苏省制浆造纸科学与技术重点实验室，江苏南京，210037 | | 熊智新1 | 1.南京林业大学江苏省制浆造纸科学与技术重点实验室，江苏南京，210037 |
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| Abstract: |
| There are the characteristics such as high hysteresis, non-linear and time varying in papermaking process, and strong couplings are formed between basis weight and moisture content of the paper. In order to solve the coupling problem, a PID decoupling controller based on the identifier of RBF neural network is proposed. This controller can identify the system model and self-adjust the PID parameters by using RBF network to realize the decoupling control .The simulation results prove that the controller can improve the dynamic and static characteristics of the control system, and is suited to paper basis weight and moisture decoupling control. |
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