Banca de DEFESA: THIAGO DE ARAUJO BRITO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : THIAGO DE ARAUJO BRITO
DATE: 26/07/2023
TIME: 08:00
LOCAL: Sala virtual Google Meet
TITLE:

Genetic algorithm optimization of the fuzzy controler of the water level and the pressure of a tube boiler

KEY WORDS:

Boiler, Control, Artificial Intelligence, Fuzzy, Genetic Algorithm.

PAGES: 77
BIG AREA: Engenharias
AREA: Engenharia Mecânica
SUBÁREA: Projetos de Máquinas
SPECIALTY: Controle de Sistemas Mecânicos
SUMMARY:

Faced with the constant technological evolutions that modern society experiences, industries have evolved more and more in search of greater efficiency and reliability of their processes. The search for new methods to optimize the industrial activities has fueled the interest in the development of research focused on this area. Despite the various technological developments that industries constantly undergo, steam remains present in their processes since the first industrial revolution, being used to perform movements in machines, which revolutionized the production process of the time. Nowadays its presence remains vast in different types of industry, being widely used for heating and electricity generation. The equipment used for steam generation is the boiler. In the process of generating steam in a boiler, there are two variables of great importance for control, which are the water level and the steam pressure in the drum. The control of these variables guarantees the operational safety of the machine and compliance with the process parameters through the required steam pressure. Thus, the boiler control problem is of great interest in academia and industry. In order to control the variables reported, it is basically necessary to act on the water supply and saturated steam exit valves of the drum. Based on this, this work aims to control the water level and pressure in the drum of a water-tube boiler through artificial intelligence in order to avoid unwanted variations in level and pressure when going through load variations. For this, fuzzy controllers optimized by genetic algorithm are used. Tests were performed for the model and their results were satisfactory.

COMMITTEE MEMBERS:
Externo ao Programa - 350693 - ANDRE LAURINDO MAITELLI - UFRNInterno - 1328152 - CARLOS EDUARDO TRABUCO DOREA
Presidente - 1451883 - FABIO MENEGHETTI UGULINO DE ARAUJO
Externo à Instituição - OSCAR GABRIEL FILHO - PETROBRAS