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Control method of penicillin production process based on collaborative training lwpls

A collaborative training and production process technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve problems such as limiting prediction effect, ignoring unlabeled data, and wasting unlabeled data

Inactive Publication Date: 2017-12-12
ZHEJIANG UNIV
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Problems solved by technology

However, when the number of training samples is small, the traditional multivariate statistical methods often fail to achieve effective prediction accuracy; in addition, the traditional multivariate statistical learning methods are often used Data that includes auxiliary variables and corresponding leading variable information, that is, what we call labeled data, and data that does not have corresponding leading variables that only contain auxiliary variable information, that is, what we call unlabeled data, is often ignored
Models built using existing labeled data are often not accurate enough, and unlabeled data with certain useful information is wasted. This shortcoming of traditional methods greatly limits their predictive effect

Method used

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  • Control method of penicillin production process based on collaborative training lwpls
  • Control method of penicillin production process based on collaborative training lwpls
  • Control method of penicillin production process based on collaborative training lwpls

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Embodiment Construction

[0049] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0050] The present invention is a locally weighted partial least squares soft sensor modeling method based on a collaborative training algorithm. The method aims at the soft sensor modeling problem in the penicillin production process. Labeled data of variable information and unlabeled data containing only auxiliary variables, and then use the labeled data to establish two initial models with considerable differences, and then use unlabeled data on the basis of the initial model to train the two models The set is iteratively updated. When a certain number of iterations or termination conditions are reached, the update of the model is stopped, and a new model is established using the final training data to realize the soft sensor modeling of the penicillin production process. Store the model parameters in the database for later use.

[0051] ...

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Abstract

The invention discloses a control method of a penicillin production process of cooperative training and Local Weighted Partial Least Squares (LWPLS), and the control method is used for soft measurement modeling under the condition that the quantity modeling data is relatively small and realizing prediction of product information of a penicillin production process. According to the control method, an effective linear prediction model is established by using a cooperative training-based local weighted partial least squares learning method, the problem of low model precision under the condition that the quantity of sampling data of the penicillin production process is too small is overcome, and the predication accuracy and the performance of the model established directing at the process are improved, thereby enabling the penicillin production process to be more reliable, and enabling the product quality to be more stable.

Description

technical field [0001] The invention belongs to the field of penicillin production process prediction and control, and in particular relates to a soft sensor modeling method based on a small number of samples and using a collaborative training algorithm and a local weighted partial least squares algorithm. Background technique [0002] In the production process of penicillin, the detection and control of penicillin product concentration is of vital significance. Due to the cost of detection equipment, the difficulty of component detection, time lag and other factors, soft sensing methods are often used in the production process of penicillin to predict the concentration information of penicillin. In the industrial process, the important variables like the penicillin concentration are called the leading variables, and some other easily measurable variables are called the auxiliary variables. Soft measurement refers to the technical method of using auxiliary variables to pred...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/041
Inventor 葛志强包亮
Owner ZHEJIANG UNIV
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