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Cross-directional Basis Weight Measure and Control System Based on CARMA Model Predictive Function Control Algorithm

机译:基于Carma模型预测功能控制算法的横向基重度量和控制系统

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According to the analysis of papermaking process, combined with the principle of cross-directional basis weight (BW) detecting and controlling, predictive function control based on CARMA (Controlled Auto Return Integral Moving Average Model) model is proposed to solve the problem of time delay, nonlinearity and uncertainty of the multi-dimension system. Simulations show that multivariable predictive functional control algorithm for fast tracking velocity, good dynamic performance, and it can effectively reduce the mutual coupling effects between variables. The method has the feasibility of applying to practical papermaking process.
机译:根据造纸过程的分析,结合横向基重(BW)检测和控制原理,提出了基于CARMA(受控自动返回积分移动平均模型)模型的预测功能控制来解决时间延迟问题多维系统的非线性和不确定性。仿真显示,多变量预测功能控制算法快速跟踪速度,动态性能良好,它可以有效地降低变量之间的相互耦合效应。该方法具有应用实用造纸过程的可行性。

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