In industries, it is difficult to measure physical quantities such as product quality. In order to estimate it, soft sensors have been proposed. In recent years, the Just-In-Time (JIT) method has attracted attention. According to this method, the output is estimated by extracting data from the database similar to the current situation. On the other hand, a database-driven control system has been proposed in which the JIT is equipped with a learning algorithm. This method calculates the control parameters using a database and has the scheme to learn the control parameters to minimize the control error. This paper proposes a new design method for soft sensors which uses a database-driven approach. Specifically, this paper proposes a method to improve the estimation accuracy without modifying the stored past data by introducing a new modifier c into the learning algorithm. Furthermore, a control system is designed in which the estimated value using the soft sensor is fed back.

中文翻译：

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数据库驱动软传感器的设计及其在控制系统中的应用

在工业中，很难测量产品质量等物理量。为了估计它，已经提出了软传感器。近年来，准时制（JIT）方法引起了人们的关注。根据这种方法，通过从数据库中提取与当前情况相似的数据来估计输出。另一方面，已经提出了一种数据库驱动的控制系统，其中 JIT 配备了学习算法。该方法使用数据库计算控制参数，并具有学习控制参数以最小化控制误差的方案。本文提出了一种新的软传感器设计方法，该方法使用数据库驱动的方法。具体来说，本文提出了一种通过引入新的修改器在不修改存储的过去数据的情况下提高估计精度的方法c进入学习算法。此外，设计了一个控制系统，其中反馈使用软传感器的估计值。