大数据驱动的在线预测控制数字生态系统框架

A. Suleykin, N. Bakhtadze, P. Panfilov
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引用次数: 1

摘要

本文建立了在线预测控制系统的大数据驱动数字生态系统框架(BDDDEF)。提出的框架由不同的Agent组成,其中每个Agent是一个分布式的虚拟服务。在我们的工作中,我们为构建在线控制数字生态系统中的大数据挑战提供解决方案,包括高容量、高速度和多种数据,以及对低数据延迟的需求。我们建议使用BDDDEF为在线预测控制系统构建鲁棒、可靠、容错、可扩展和高负载的数据管道。我们回顾了在线预测控制体系结构的大数据主要系统,回顾了在线控制系统数字生态系统设计的文献,设计并描述了框架的主要特征、主要架构组件和功能架构,最后提出了用于在线预测的新的预测控制方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big-Data Driven Digital Ecosystem Framework for Online Predictive Control
In this paper, Big-Data Driven Digital Ecosystem Framework (BDDDEF) for Online Predictive Control Systems is created. The proposed framework consists of different Agents, where each Agent is a distributed and virtual service. In our work, we provide solutions to the Big Data challenges in building Digital Ecosystems for Online Control including high volumes, velocity and variety of data, and the need for low data latency. We propose to use BDDDEF for building robust, reliable, fault-tolerant, scalable and high-loaded data pipelines for Online Predictive Control Systems. We review Big Data Main Systems for Online Predictive Control Architecture, review the literature for Digital Ecosystems design for Control Systems Online, design and describe main features, main architectural components and functional architecture of the framework, and finally, propose new Predictive Control methodology for Online Predictions.
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