基于 MSVR 和操作员的微反应器设备智能 MIMO 无传感器控制系统设计

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Computation Pub Date : 2023-12-25 DOI:10.3390/computation12010002

Tatsuma Kato, Kosuke Nishizawa, Mingcong Deng

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引用次数: 0

摘要

最近，能够进行快速、高效化学反应的管状反应器--微反应器备受关注。然而，由于反应热引起的温度变化会导致反应的进行与设计不同，因此需要精确的温度控制。在之前的研究中，有人提出了一种单输入/输出非线性控制系统，使用的模型是将微反应器分为三个区域，并考虑温度梯度制定热方程，但该系统无法控制两个不同的温度。本文利用算子理论设计了一种多输入、多输出非线性控制系统。另一方面，当并行微反应器的数量增加时，从降低成本的角度出发，将使用广义高斯核的 M-SVR 的无传感器控制方法纳入 MIMO 非线性控制系统，并通过实验结果证实了所提方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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MSVR & Operator-Based System Design of Intelligent MIMO Sensorless Control for Microreactor Devices

Recently, microreactors, which are tubular reactors capable of fast and highly efficient chemical reactions, have attracted attention. However, precise temperature control is required because temperature changes due to reaction heat can cause reactions to proceed differently from those designed. In a previous study, a single-input/output nonlinear control system was proposed using a model in which the microreactor is divided into three regions and the thermal equation is formulated considering the temperature gradient, but it could not control two different temperatures. In this paper, a multi-input, multi-output nonlinear control system was designed using operator theory. On the other hand, when the number of parallel microreactors is increased, a sensorless control method using M–SVR with a generalized Gaussian kernel was incorporated into the MIMO nonlinear control system from the viewpoint of cost reduction, and the effectiveness of the proposed method was confirmed via experimental results.

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来源期刊

Computation Mathematics-Applied Mathematics

CiteScore

3.50

自引率

4.50%

发文量

201

审稿时长

8 weeks

期刊介绍： Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.