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Estudo da aplicabilidade de algoritmos de aprendizado por reforço em um pêndulo invertido

This work addresses an exploratory research on the applicability of reinforcement learning algorithms (RLA) in an inverted pendulum system, a classic problem of an unstable open loop system. The research carried out, addressed the study and application of some specific algorithms such as Q-Learning...

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Principais autores: Acuña, Daniel Grimm, Luz, Henrique Santos da, Klein, Lucas Jurgen
Formato: Trabalho de Conclusão de Curso (Graduação)
Idioma: Português
Publicado em: Universidade Tecnológica Federal do Paraná 2020
Assuntos:
Algoritmos
Controle automático
Kalman, Filtragem de
Markov, Processos de
Aprendizado por reforço
Algorithms
Automatic control
Kalman filtering
Markov processes
Reinforcement learning
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::MEDIDAS ELETRICAS, MAGNETICAS E ELETRONICAS INSTRUMENTACAO::SISTEMAS ELETRONICOS DE MEDIDA E DE CONTROLE
Acesso em linha: http://repositorio.utfpr.edu.br/jspui/handle/1/8198
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Resumo: This work addresses an exploratory research on the applicability of reinforcement learning algorithms (RLA) in an inverted pendulum system, a classic problem of an unstable open loop system. The research carried out, addressed the study and application of some specific algorithms such as Q-Learning and Deep-Q-Networks. The work presents a theoretical research of the algorithms until the software implementation of the same ones. In a second step, a physical prototype of the pendulum system was built, in which stochastic filters were used in order to enhance the sensor reading quality, leaving open a possibility of continuity of the development for future works.

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