CAJ | 학술논문

为了降低递推部分最小二乘（RPLS）建模方法的模型校正频率，开发了一种基于模型性能评估的 RPLS （MPA-RPLS）模型。首先，根据过程的初始特性，自动生成模型的置信限，以均方根误差（RMSEP）为性能指标，评估模型性能；依据模型性能的评估结果，选择性地启动模型校正和置信限校正。然后，引入滑动平均滤波器消除过程变量中的噪声，探讨噪声对模型性能的影响程度。最后，将MPA-RPLS模型应用于一个化学反应过程——C8芳烃临氢异构化过程，基于大量工业数据，进行仿真验证。仿真结果表明：本文开发的模型仅以微小的精度损失换取了模型计算效率的大幅提高（即模型校正频率大幅下降）；滑动平均滤波器可有效地处理变量的噪声，改善模型的预测精度。
위료강저체추부분최소이승（RPLS）건모방법적모형교정빈솔，개발료일충기우모형성능평고적 RPLS （MPA-RPLS）모형。수선，근거과정적초시특성，자동생성모형적치신한，이균방근오차（RMSEP）위성능지표，평고모형성능；의거모형성능적평고결과，선택성지계동모형교정화치신한교정。연후，인입활동평균려파기소제과정변량중적조성，탐토조성대모형성능적영향정도。최후，장MPA-RPLS모형응용우일개화학반응과정——C8방경림경이구화과정，기우대량공업수거，진행방진험증。방진결과표명：본문개발적모형부이미소적정도손실환취료모형계산효솔적대폭제고（즉모형교정빈솔대폭하강）；활동평균려파기가유효지처리변량적조성，개선모형적예측정도。
In order to reduce the model updating frequency of recursive partial least squares (RPLS) modeling methods, a RPLS model based on the model performance assessment (MPA-RPLS) is developed. Firstly, a confidence limit of the model is generated automatically based on the initial behavior of a process. And a root mean squared error of prediction (RMSEP) is used as a performance index to evaluate the model. Base on the results of the model performance assessment, the model updating is selectively activated, in the meanwhile, the confidence limit is also updated. Subsequently, a moving average filter is integrated into the model to eliminate the noise embbeded in variables, and the effect of the noise on the model performance is then investigated. At last, the developed model is applied to a chemical reaction process, hydro-isomerization process of C8-aromatics. Simulation is run based on a large number of industrial data. The simulation results show that the computational efficiency is improved greatly (model updating frequency is reduced greatly) by the developed model, while a minor loss of the prediction accuracy is found. The noise embedded in variables could be dealt with effectively by the moving average filter, hence the prediction accuracy is improved.