MONITORING AND CONTROLLING OF INDUSTRIAL AUTOMATION SYSTEM CONSIDERING VAGUE INPUTS

NASSER  NASSER; VICENTE FERREIRA DE LUCENA JUNIOR

doi:10.20906/CBA2022/502

NASSER NASSER University of Stuttgart - Institute of Industrial Automation and Software Engineering
VICENTE FERREIRA DE LUCENA JUNIOR PPGEE - Universidade Federal do Amazonas

DOI: https://doi.org/10.20906/CBA2022/502

Keywords: Fuzzy, Uncertainty, Neuronal networks, Industrial automation, Machine learning, Industrial automation HMI

Abstract

This paper presents a new model for controlling and monitoring Industrial Automation Systems. The architecture of this model does not limit it to be connected to only one specific system but makes it able to be adapted to different automation systems as well as reused for new ones, packing any industrial communication protocol. The basic components have their hard-ware and software described, as well as the interfaces with the users, with the automation system, and between components. Thus, the proposed structure is presented, and later it is shown how it is possible to reuse this system for other applications. An-other aspect of the approach is to deal with uncertain statements of the user. It allows the application to interpret these inputs. Furthermore, the application learns, over time, how to better interpret user preferences and behavior patterns.